Ali is available for hire
Hire AliAli Ashfaq
Verified Expert in Engineering
Data Engineer and Developer
Lahore, Punjab, Pakistan
Toptal member since June 7, 2022
Bio
Ali is a Google Certified Professional Data Engineer with 6+ years of experience in data engineering, database design, ETL development, and data warehouse testing with Google Cloud Platform (GCP) projects. He has delivered multiple data pipelines and end-to-end ETL processes in GCP. Ali is also skilled in data modeling for enterprise data warehouse implementation projects.
Portfolio
Coca-Cola Icecek
Analytics, BigQuery, Apache Airflow, Python 3, Data Build Tool (dbt)...
BioIntelliSense, Inc.
Python, PySpark, SQL, Data Engineering, Apache, ETL, ETL Tools, Apache Kafka...
Syngenta
Neo4j, Amazon Neptune, Graph Databases, AWS Lambda, Amazon Web Services (AWS)...
Experience
- Data Engineering - 8 years
- Data Visualization - 7 years
- Google Cloud Platform (GCP) - 7 years
- Python - 7 years
- Data Analytics - 7 years
- ETL Tools - 7 years
- Talend ETL - 7 years
- BigQuery - 7 years
Preferred Environment
PyCharm, Windows, Data Warehousing, Google Sheets, Data Warehouse Design, Analytics, Ad-hoc Reporting, Business Intelligence (BI), Dashboards, Data Engineering, Snowflake, PostgreSQL, Graph Databases, Real Estate, MySQL, Back-end Development, OLTP, OLAP, APIs, Data Lakes, Cloud Firestore
The most amazing...
...EDW I've developed is a credit scoring model that streamlined the bank's loan approving and dispersing processes, increasing revenue by $500 million.
Work Experience
Senior Data Engineer
2022 - PRESENT
Coca-Cola Icecek
- Migrated SAP jobs to GCP Apache Airflow using different airflow operators. Built data pipelines in GCP using Python. Data transformations and cleansing were carried out using SQL queries and Python. Followed CI/CD best practices using GitHub.
- Managed Jira by overseeing project workflows, assigning tasks, tracking progress, and ensuring timely delivery. Implemented efficient ticketing systems and collaborated with teams.
- Facilitated efficient data exchange between SQL Server and GCP, enabling orders by pushing recommendations to a mobile app-connected database. This streamlined sales, enhanced inventory management, and boosted profitability.
Technologies: Analytics, BigQuery, Apache Airflow, Python 3, Data Build Tool (dbt), Google Analytics 4 (GA4), SAP, GitHub, SQL, Looker, Microsoft Power BI, Google Cloud Storage, Google Cloud Functions, Cloud Dataflow, Google Pub/Sub, Streaming Data, Google Compute Engine (GCE), Docker Cloud, Google Kubernetes Engine (GKE), Google Container Engine, Data Modeling, PostgreSQL, OLAP, APIs, Data Integration, Pub/Sub, Google Cloud Dataproc, Terraform, Parquet, Google Cloud, Looker Studio, HubSpot, API Integration, English, Query Optimization, Data Processing, Databricks, Unstructured Data Analysis, Dashboard Development, Reporting, Amazon Web Services (AWS), Database Administration (DBA), Data Architecture, Database Replication, Performance Tuning, Sharding, Microsoft SQL Server, Architecture, Cloud Infrastructure, Database Migration, Database Architecture, Data Structures, AWS Lambda, Node.js, Advisory, Consulting, Full-stack, Machine Learning, Infrastructure, Spark, Google Cloud Platform (GCP), Data Lake Design, ETL Tools, Google Data Studio, DAX, Amazon, Redshift, ELT, Data-level Security, Data, Data Flows, Scalability, SQL Server Integration Services (SSIS), ETL Implementation & Design, Data Transformation, Sales, Apache Spark, Data Warehouse Testing, Technical Leadership, Azure SQL Data Warehouse, JSON
Data Engineer
2025 - 2025
BioIntelliSense, Inc.
- Designed a secure, scalable BI platform on AWS, centralizing streaming device data from multiple sources to provide real-time, actionable insights for healthcare providers.
- Built Qlik Sense dashboards with row-level security, giving each client personalized access to their device data while maintaining strict privacy and compliance standards.
- Automated data processing and anomaly detection using Databricks, cutting manual effort by 70% and ensuring up-to-the-minute visibility into device performance.
- Enabled proactive monitoring and resource allocation, helping teams identify issues faster and make data-driven decisions with confidence.
- Delivered a flexible, future-ready architecture that scales securely as more devices and clients are onboarded, supporting growth and compliance seamlessly.
Technologies: Python, PySpark, SQL, Data Engineering, Apache, ETL, ETL Tools, Apache Kafka, Data Cleansing, Databricks, Snowflake, Spark, AWS IoT, Qlik Sense, Microsoft Fabric, Pipelines
Graph Database Engineer
2024 - 2024
Syngenta
- Built scalable ETL pipelines using AWS Glue to automate data transformation and loading, reducing processing time by 40% while ensuring data accuracy for large-scale agricultural datasets.
- Developed and deployed API integrations using AWS Lambda to connect external data sources with internal systems, improving real-time data accessibility and reducing latency for mission-critical operations.
- Leveraged AWS Glue workflows and Lambda functions to support real-time analytics, improving decision-making for data-driven applications in the agriculture sector.
Technologies: Neo4j, Amazon Neptune, Graph Databases, AWS Lambda, Amazon Web Services (AWS), Node.js, AWS Glue, Redshift, Data Migration, Data Transformation, Database Design, Database Schema Design, Technical Leadership, Azure Service Fabric, Microsoft Fabric, Microsoft Azure
Data Analyst
2024 - 2024
Bach App Inc
- Integrated and streamlined data ingestion pipelines by consolidating data from third-party ETL tools like Hevo and Stitch, as well as the client’s proprietary application data, into a centralized Google BigQuery data warehouse.
- Collaborated extensively with the client to understand their complex customer classification model, including detailed segmentation and multi-dimensional attributes, and translated these requirements into a structured schema in BigQuery.
- Designed and implemented custom data transformations in BigQuery to create tables and views that accurately reflected the client’s intricate customer classifications, ensuring consistency and scalability.
- Automated the processing of ingested data using BigQuery scheduled queries and Cloud Functions, ensuring the data remained up-to-date and ready for analysis.
- Created interactive dashboards on Looker Studio, visualizing critical metrics and KPIs tailored to the client’s business model, enabling them to gain actionable insights into customer behavior and marketing performance.
- Built dynamic reporting workflows using Google Sheets integrated with BigQuery, enabling quick ad-hoc analysis and easy access for non-technical stakeholders.
Technologies: Data Engineering, ETL, Looker, Looker Studio, BigQuery, Google BigQuery, Google Data Studio, Dashboards, Data Analysis, Data Science, Data Transformation, Apache Spark, Optical Character Recognition (OCR), Technical Leadership, Microsoft Fabric
Marketing Scientist and Business Intelligence Analyst
2024 - 2024
Tawkify, Inc.
- Designed and implemented a comprehensive Sigma Compute Dashboard, enabling the client to track daily traffic trends and marketing spend, resulting in improved campaign performance monitoring.
- Uncovered and presented actionable insights from data analysis, empowering the business to make informed, data-driven decisions that enhanced strategic planning.
- Generated multiple reports to analyze frequently purchased packages, correlating trends with UTM campaign parameters to optimize marketing efforts and improve ROI.
- Identified critical data quality issues and proactively communicated their impact to the engineering team, streamlining data accuracy and reliability for reporting.
- Developed an in-depth User Behavior Dashboard to analyze and compare user versus client demographics, providing actionable insights to tailor marketing strategies.
Technologies: Business Intelligence (BI), Data Visualization, Marketing Analytics, Marketing Reports, Tableau, Business Intelligence (BI) Platforms, Microsoft Excel, Google Tag Manager, Mixpanel, Data Analytics, Marketing Strategy, Marketing Campaigns, Marketing Technology (MarTech), TikTok, Data Transformation, Sales, Apache Spark, Technical Leadership, Microsoft Fabric
BigQuery Expert
2024 - 2024
Peerly Inc
- Structured and optimized a 4TB dataset within BigQuery, leading to a 50% improvement in query performance and data retrieval times.
- Created multiple materialized views to enhance data analysis capabilities, facilitating faster and more accurate reporting for the client's P2P texting platform.
- Enhanced data ingestion pipelines from Pub/Sub and SQL external connections, ensuring seamless and efficient data flow into BigQuery, reducing latency by 30%.
- Assisted the client's team with architectural best practices in BigQuery, elevating their understanding and proficiency, which resulted in a 40% increase in team efficiency.
Technologies: Google Cloud Platform (GCP), BigQuery, Google Pub/Sub, Data Lake Design, ETL Tools, API Integration, ELT, Data-level Security, Data, Data Flows, SQL Server Integration Services (SSIS), Microsoft Fabric
Graph DB Expert
2024 - 2024
Syngenta - Digital Product Engineering - Brazil 2024
- Developed and implemented graph database optimizations using Neo4j and AWS Neptune, resulting in a 40% reduction in query response time and improved data retrieval efficiency.
- Designed and deployed serverless functions with AWS Lambda to automate data processing workflows, reducing operational overhead by 30%.
- Created and maintained Node.js applications to facilitate seamless data integration and processing across various systems, enhancing data flow and system interoperability.
- Conducted comprehensive assessments to identify and resolve system bottlenecks, significantly improving the client's data processing capabilities.
- Leveraged AWS cloud services, including Lambda, S3, and EC2, to build scalable and reliable data pipelines, ensuring high availability and performance.
Technologies: Neo4j, Amazon Neptune, Graph Databases, AWS Lambda, Amazon Web Services (AWS), Node.js, Data Lake Design, ETL Tools, ELT, Data-level Security, Data, Data Flows, SQL Server Integration Services (SSIS), Data Transformation
Lead Data Engineer, Web Analytics and Insights
2023 - 2024
Dr. Barbara Sturm
- Engineered an advanced ETL pipeline that consolidated Clickstream data into Google BigQuery, enhancing data-driven strategies for a leading European online cosmetic retailer.
- Developed complex SQL queries in BigQuery, processing and analyzing vast datasets to optimize digital marketing efforts, resulting in measurable improvements in customer engagement and sales.
- Implemented and fine-tuned data visualizations in Looker Studio, presenting real-time sales, vouchers, and promotional data, which significantly supported decision-making processes for marketing and sales teams.
- Streamlined the integration of Google Analytics data into BigQuery, employing custom SQL scripts to extract nuanced insights into user behavior, which informed and enhanced the online retail marketing strategy for a premier skincare brand.
Technologies: Python, SQL, Google Cloud Platform (GCP), Google BigQuery, Looker Studio, Google Cloud Functions, Google Cloud Dataproc, Google Analytics 4 (GA4), Database Analytics, Web Analytics, Social Media Web Traffic, Digital Marketing, Dashboards, English, Query Optimization, Data Processing, Databricks, REST APIs, Unstructured Data Analysis, Dashboard Development, Reporting, Database Administration (DBA), Data Architecture, Database Performance, Database Replication, Performance Tuning, Sharding, Microsoft SQL Server, Architecture, Cloud Infrastructure, Databases, Database Migration, Database Architecture, Data Structures, SQL Server DBA, AWS Lambda, Node.js, Advisory, Consulting, Full-stack, Infrastructure, BigQuery, Data Lake Design, Data Visualization, ETL Tools, Google Data Studio, API Integration, ELT, Data-level Security, Data, Data Flows, Startups, Business Intelligence (BI) Platforms, Marketing Analytics, Azure Cosmos DB, PySpark, Data Transformation, Apache Spark
Data Analyst
2023 - 2024
Uptraded GmbH
- Analyzed user interaction data within the Uptraded app using Mixpanel, providing insights that led to a 20% improvement in user conversion rates over four weeks.
- Streamlined the data collection framework to ensure the capture of meaningful analytics, optimizing the Mixpanel set up for future data-driven strategies.
- Conducted in-depth analysis of secondhand fashion consumer trends, contributing to a platform overhaul that emphasized circular fashion and increased app retention by 15%.
- Collaborated with cross-functional teams, translating complex data into actionable strategies aligned with Uptraded's mission of sustainable fashion consumption.
- Facilitated knowledge transfer sessions for the Uptraded team, empowering them with the analytical skills necessary to leverage Mixpanel for ongoing conversion optimization initiatives.
Technologies: Data Analytics, Mixpanel, eCommerce, API Integration, English, Query Optimization, Data Processing, REST APIs, Unstructured Data Analysis, Dashboard Development, Reporting, Database Administration (DBA), Data Architecture, Database Performance, Database Replication, Performance Tuning, Sharding, Microsoft SQL Server, Architecture, Back-end, Cloud Infrastructure, Databases, Database Migration, Database Architecture, Data Structures, Advisory, Consulting, Full-stack, Infrastructure, Google Cloud Platform (GCP), BigQuery, Data Lake Design, Data Visualization, Google Data Studio, Data-level Security, Data, Data Flows, Startups, Business Intelligence (BI) Platforms
GCP Data Engineer
2022 - 2024
Patrianna Limited
- Led the optimization of ETL processes on GCP, which reduced data processing times by 40%, enhancing the app's performance for end-users.
- Collaborated with a team of data analysts and financial experts to translate complex financial concepts into clear, actionable insights within the app, driving a user satisfaction score increase of 20%.
- Implemented BigQuery solutions to handle complex queries over large datasets, enabling the app to calculate projected savings growth and net worth estimations rapidly.
- Orchestrated secure and compliant data storage mechanisms using Cloud Storage with encryption at rest and in transit, adhering to financial data security regulations and best practices.
- Automated data ingestion workflows using Cloud Dataflow and Cloud Composer, ensuring efficient and error-free data updates across user accounts for accurate financial tracking.
Technologies: Google BigQuery, Google Cloud Platform (GCP), SQL, ETL, Parquet, PostgreSQL, R, Cloud Dataflow, Spark SQL, Azure Databricks, Azure, Azure Synapse, Azure Data Factory (ADF), English, Query Optimization, Data Processing, Unstructured Data Analysis, Dashboard Development, Reporting, Amazon Web Services (AWS), Data Architecture, Database Performance, Database Replication, Performance Tuning, Architecture, Cloud Infrastructure, Databases, Database Migration, Database Architecture, Data Structures, SQL Server DBA, Node.js, Advisory, Consulting, Full-stack, Machine Learning, Infrastructure, Neo4j, BigQuery, Data Lake Design, ETL Tools, Talend ETL, Google Data Studio, API Integration, ELT, Data-level Security, Data, Data Flows, Scalability, SQL Server Integration Services (SSIS), Data Transformation, Sales, Apache Spark, Fivetran, Microsoft Azure
Senior Data Engineer
2022 - 2023
Tealbook
- Developed a robust web scraping solution using Python, Scrapy, and Selenium. This enabled the efficient extraction of certification data from various sources. I transformed and preprocessed the data using Apache Airflow, ensuring consistency and quality.
- Collaborated with cross-functional teams, using data engineering best practices. Leveraging DBT, I defined data models and ETL processes. Robust data-quality checks and monitoring mechanisms addressed integrity and consistency issues.
- Benefited from reliable and accurate certification data that supports informed decision-making and drives business growth.
Technologies: Analytics, Apache Airflow, BigQuery, Business Intelligence (BI), Dashboards, Data Analysis, Ad-hoc Reporting, Data Build Tool (dbt), Data Engineering, Data Analytics, Data Pipelines, Scrapy, Selenium, Python, Data Visualization, Data Science, Data Warehousing, Data Modeling, OLAP, APIs, Data Integration, Terraform, Parquet, Google Cloud, MongoDB, Looker Studio, HubSpot, English, Query Optimization, Data Processing, Unstructured Data Analysis, Dashboard Development, Reporting, Data Architecture, Performance Tuning, Architecture, Cloud Infrastructure, Databases, Database Migration, Database Architecture, Data Structures, SQL Server DBA, AWS Lambda, Node.js, Advisory, Consulting, Full-stack, Machine Learning, Infrastructure, Spark, Neo4j, Google Cloud Platform (GCP), ETL Tools, Talend ETL, API Integration, ELT, Data-level Security, Data, Data Flows, SQL Server Integration Services (SSIS), Data Transformation
Senior Data Analytics Consultant
2020 - 2022
Systems Limited
- Built and architected multiple data pipelines and end-to-end ETL processes for data ingestion and transformation in GCP.
- Prepared and coordinated tasks among the team I managed.
- Designed and created various layers of the data lake.
- Executed test cases to identify potential issues with ETL jobs and ensure data sanity and integrity in the database.
- Integrated more than 20 sources to give customers a 360-degree view.
Technologies: Data Analytics, Data Science, Data Engineering, Data Visualization, Google Cloud Platform (GCP), BigQuery, Google Data Studio, Apache Airflow, Google Cloud Functions, Google Compute Engine (GCE), Neo4j, Python, Google BigQuery, SQL, ETL, PostgreSQL, Data Pipelines, Data Warehousing, Dashboards, Business Intelligence (BI), Google Analytics, Microsoft Excel, Data Analysis, Screaming Frog, Google Sheets, Google Search Console, Google SEO, Microsoft Power BI, SEO Tools, Technical Project Management, Search Engine Optimization (SEO), Data Warehouse Design, Looker, Data Build Tool (dbt), Analytics, Ad-hoc Reporting, Data Modeling, Graph Databases, Real Estate, MySQL, Back-end Development, OLAP, APIs, Data Integration, Terraform, Parquet, Google Cloud, MongoDB, Looker Studio, API Integration, Query Optimization, Data Processing, Unstructured Data Analysis, Dashboard Development, Reporting, Data Architecture, Performance Tuning, Architecture, Back-end, Cloud Infrastructure, Apache Beam, Databases, Database Migration, Database Architecture, Data Structures, Advisory, Consulting, Full-stack, Infrastructure, Power Query, Data-level Security, Data, Data Flows, Business Intelligence (BI) Platforms, Marketing Analytics, ETL Implementation & Design, Data Transformation, Apache Spark, Fivetran, Jupyter
ETL/BI Developer
2017 - 2020
Analytics Private Limited
- Managed and mentored a team of five resources and collaborated with clients to understand data needs and maintain a close working relationship.
- Performed data modeling and led an enterprise data warehouse (EDW) implementation project.
- Designed and developed end-to-end ETL pipelines and tested processes for data validation before loading it into a data warehouse.
- Identified and implemented methodologies to ensure data integrity and quality.
Technologies: Data Engineering, ETL Tools, Talend ETL, IBM InfoSphere (DataStage), Tableau, IBM Cognos, SQL, ETL, Data Pipelines, Data Warehousing, Dashboards, Business Intelligence (BI), Technical Project Management, Data Warehouse Design, Data Build Tool (dbt), Analytics, Ad-hoc Reporting, Data Modeling, PostgreSQL, Real Estate, MySQL, Back-end Development, OLTP, OLAP, APIs, Data Integration, Parquet, MongoDB, Looker Studio, API Integration, Query Optimization, Data Processing, Unstructured Data Analysis, Dashboard Development, Reporting, Data Architecture, Performance Tuning, Architecture, Cloud Infrastructure, Databases, Database Migration, Database Architecture, Data Structures, Advisory, Consulting, Full-stack, Infrastructure, Data Visualization, Google Data Studio
Experience
Core Modules for Easy Buy
Built the core modules of one of the biggest eCommerce systems in the USA.
The project used analytics and business intelligence (BI) to improve customer experience and engagement, retain potential customers, offer them the best choice, enhance the system's efficiency, and increase sales based on historical and incremental data.
I designed and built multiple end-to-end ETL processes for data ingestion and transformation in the Google Cloud Platform (GCP) and coordinated tasks among the team. The core modules allowed the system to integrate data from various heterogeneous source platforms, including Google Cloud, Amazon S3 bucket, MuleSoft API, and SFTP. It also featured the ETL process by incorporating data in the GCP deep learning and BigQuery DWH and ingesting the data in the Neo4J graph database.
I used Python, SQL, and GCP stack for data processing and Apache Airflow for data orchestration during the project. I used the Google Cloud function with Python to load data into BigQuery for on-arrival CSV files in the Google Cloud Storage (GCS) bucket and maintained raw file archival in the cloud storage.
The project used analytics and business intelligence (BI) to improve customer experience and engagement, retain potential customers, offer them the best choice, enhance the system's efficiency, and increase sales based on historical and incremental data.
I designed and built multiple end-to-end ETL processes for data ingestion and transformation in the Google Cloud Platform (GCP) and coordinated tasks among the team. The core modules allowed the system to integrate data from various heterogeneous source platforms, including Google Cloud, Amazon S3 bucket, MuleSoft API, and SFTP. It also featured the ETL process by incorporating data in the GCP deep learning and BigQuery DWH and ingesting the data in the Neo4J graph database.
I used Python, SQL, and GCP stack for data processing and Apache Airflow for data orchestration during the project. I used the Google Cloud function with Python to load data into BigQuery for on-arrival CSV files in the Google Cloud Storage (GCS) bucket and maintained raw file archival in the cloud storage.
EDW for a Private Credit Bureau
https://tasdeeq.com/Created a credit scoring model to streamline the bank's loan approval and dispersing processes, which increased revenue by $500 million.
My main contributions included the ETL process, EDW architecture, and aggregated data set (ADS), using technologies such as Vertica, IBM InfoSphere DataStage, and IBM Cognos.
I developed the model's architecture that was successfully launched with over 90% accuracy and efficiency. It features the ETL process of extracting loan/lease transactional data from 70+ financial institutions and loading the transformed data into the DWH.
I also prepared an ADS to aid the formation of the statistical model. It can predict and categorize the customer/borrower as either good, average, or bad and assign a default probability to every customer based on the information provided to the model.
My main contributions included the ETL process, EDW architecture, and aggregated data set (ADS), using technologies such as Vertica, IBM InfoSphere DataStage, and IBM Cognos.
I developed the model's architecture that was successfully launched with over 90% accuracy and efficiency. It features the ETL process of extracting loan/lease transactional data from 70+ financial institutions and loading the transformed data into the DWH.
I also prepared an ADS to aid the formation of the statistical model. It can predict and categorize the customer/borrower as either good, average, or bad and assign a default probability to every customer based on the information provided to the model.
Unified Analytics Solution for Locallogy
I empowered Locallogy, a small business digital marketing agency, with a comprehensive data warehouse solution that revolutionized its in-depth analysis capabilities. This solution enabled me to consolidate and analyze data from multiple sources, providing powerful insights through a unified dashboard.
To achieve this, I designed a robust data flow incorporating data from various APIs, such as Screaming Frog and AWR (Advanced Web Ranking). I created a potent combination of data sources by integrating Google Analytics and Google Search Console with BigQuery. Additionally, I implemented an interface on Google Sheets, seamlessly connected to BigQuery, facilitating collaboration across the organization. This adaptable solution allowed the team to efficiently insert, update, and delete data from BigQuery, enhancing their ability to deliver robust digital marketing solutions for their clients.
From a technical perspective, I leveraged several Google Cloud Platform (GCP) services, including Compute Engine, Cloud Scheduler, and BigQuery. I employed VM instances running Python ETL scripts to capture and process data, ensuring seamless integration with the APIs.
To achieve this, I designed a robust data flow incorporating data from various APIs, such as Screaming Frog and AWR (Advanced Web Ranking). I created a potent combination of data sources by integrating Google Analytics and Google Search Console with BigQuery. Additionally, I implemented an interface on Google Sheets, seamlessly connected to BigQuery, facilitating collaboration across the organization. This adaptable solution allowed the team to efficiently insert, update, and delete data from BigQuery, enhancing their ability to deliver robust digital marketing solutions for their clients.
From a technical perspective, I leveraged several Google Cloud Platform (GCP) services, including Compute Engine, Cloud Scheduler, and BigQuery. I employed VM instances running Python ETL scripts to capture and process data, ensuring seamless integration with the APIs.
Optimizing Decision-making with M&M Data Warehouse Architecture
The M&M Data Warehouse architecture was developed to optimize the integration of large datasets extracted from multiple heterogeneous source systems. This architecture aims to enhance the efficiency of the decision-making process for Marcus & Millichap's legal property system in the United States.
By streamlining the information flow, it enables better insights and more informed decision-making. The M&M Data Warehouse architecture encompasses multiple areas, including the extract, transform, load (ETL) process, which ensures seamless data incorporation into the warehouse after transformation and cleaning.
By streamlining the information flow, it enables better insights and more informed decision-making. The M&M Data Warehouse architecture encompasses multiple areas, including the extract, transform, load (ETL) process, which ensures seamless data incorporation into the warehouse after transformation and cleaning.
Data Engineering for an Online Cosmetic Retailer
https://eu.drsturm.com/As a senior data engineer for Eu.drsturm.com, an online cosmetic retailer operating in Europe and America, I spearheaded the integration and analysis of complex data sets from Clickstream into BigQuery. My role encompassed architecting and executing a robust ETL pipeline to efficiently transport data, utilizing Dataproc for advanced processing and optimization tasks. I was instrumental in transforming raw data into actionable insights, which were visualized through Looker Studio. This enabled the visualization of critical business metrics, including sales performance, voucher redemption rates, and the effectiveness of promotional campaigns. My contributions were pivotal in enhancing data-driven decision-making, optimizing marketing strategies, and ultimately driving the company's growth. My work showcased not only my technical expertise but also my ability to collaborate closely with cross-functional teams to align data analytics with business objectives.
BI Solution for Crowdbotics
https://www.crowdbotics.com/I significantly enhanced the performance of an intermediary company by delivering a robust business intelligence solution.
By implementing an end-to-end data pipeline, I successfully gathered, transformed, and loaded data from various sources, such as Heroku, Stripe, HubSpot, Toggl, and Google Sheets, into a centralized storage system BigQuery Data warehouse. The system included comprehensive dashboards tailored for executives, project managers, team leads, and recruitment departments, enabling them to make quick, informed, data-driven decisions.
I used DBT and SQL in this project, integrating with GitHub. To accommodate the substantial volume of daily data generated by over 5000+ projects and 1000+ developers, I designed and implemented efficient ETL (Extract, Transform, Load) jobs.
These jobs seamlessly combined data from multiple sources, resulting in a unified and reliable source of truth for the organization. Through this implementation, the company gained a comprehensive and streamlined data infrastructure, providing accurate insights for enhanced decision-making.
Technically, the core data model was designed using DBT, GCP Bigquery SQL, and Looker.
By implementing an end-to-end data pipeline, I successfully gathered, transformed, and loaded data from various sources, such as Heroku, Stripe, HubSpot, Toggl, and Google Sheets, into a centralized storage system BigQuery Data warehouse. The system included comprehensive dashboards tailored for executives, project managers, team leads, and recruitment departments, enabling them to make quick, informed, data-driven decisions.
I used DBT and SQL in this project, integrating with GitHub. To accommodate the substantial volume of daily data generated by over 5000+ projects and 1000+ developers, I designed and implemented efficient ETL (Extract, Transform, Load) jobs.
These jobs seamlessly combined data from multiple sources, resulting in a unified and reliable source of truth for the organization. Through this implementation, the company gained a comprehensive and streamlined data infrastructure, providing accurate insights for enhanced decision-making.
Technically, the core data model was designed using DBT, GCP Bigquery SQL, and Looker.
Automated Payroll & Sales Analytics
Built an end-to-end payroll automation and sales performance analytics platform for a nationwide retail chain in North America.
The platform used data and BI to simplify payroll, automate sales-based bonuses, and give managers clear, real-time visibility into store performance. This helped improve accuracy, boost employee satisfaction, and support smarter operational decisions.
I designed and implemented ETL pipelines to ingest and transform data from SFTP servers, timecards, and sales systems into BigQuery, using Python, SQL, and DBT. Payroll and bonus calculations were automated via Cloud Functions, Cloud Scheduler, and Stored Procedures, while raw and processed data were securely archived.
Power BI dashboards provided actionable insights into payroll, incentives, and store KPIs, enabling leadership to make faster, data-driven decisions. The solution scaled across multiple locations, improving efficiency, transparency, and workforce management.
The platform used data and BI to simplify payroll, automate sales-based bonuses, and give managers clear, real-time visibility into store performance. This helped improve accuracy, boost employee satisfaction, and support smarter operational decisions.
I designed and implemented ETL pipelines to ingest and transform data from SFTP servers, timecards, and sales systems into BigQuery, using Python, SQL, and DBT. Payroll and bonus calculations were automated via Cloud Functions, Cloud Scheduler, and Stored Procedures, while raw and processed data were securely archived.
Power BI dashboards provided actionable insights into payroll, incentives, and store KPIs, enabling leadership to make faster, data-driven decisions. The solution scaled across multiple locations, improving efficiency, transparency, and workforce management.
Education
2013 - 2017
Bachelor's Degree in Computer Science
University of Central Punjab (UCP) - Lahore, Pakistan
Certifications
NOVEMBER 2022 - NOVEMBER 2024
Google Professional Cloud Architect
Google Cloud
OCTOBER 2021 - PRESENT
Microsoft Certified Azure Data Engineer Associate
Microsoft Learn
OCTOBER 2021 - OCTOBER 2023
Professional Data Engineer
Google Cloud
SEPTEMBER 2021 - PRESENT
Advanced Google Analytics
Skills
Libraries/APIs
PySpark, REST APIs, Node.js, Pandas, Stripe, Fabric
Tools
Talend ETL, Tableau, BigQuery, Apache Airflow, Google Compute Engine (GCE), Microsoft Excel, Screaming Frog, Google Sheets, Microsoft Power BI, Looker, Terraform, dbt Cloud, IBM InfoSphere (DataStage), Google Analytics, Power Query, Google Cloud Dataproc, Apache Beam, Git, PyCharm, IBM Cognos, GitHub, Cloud Dataflow, Google Kubernetes Engine (GKE), Jira, Stitch Data, Toggl, Zapier, Spark SQL, Google Cloud Composer, AWS Glue, Jupyter, Apache, Qlik Sense
Languages
Python, SQL, C++, Python 3, Snowflake, R, Java, JavaScript
Paradigms
ETL, Business Intelligence (BI), OLAP, ETL Implementation & Design, Automation, Search Engine Optimization (SEO), Database Design
Platforms
Google Cloud Platform (GCP), Azure, HubSpot, Databricks, Amazon Web Services (AWS), AWS Lambda, Microsoft Fabric, Salesforce, Amazon, Azure Synapse, Docker, RudderStack, Azure SQL Data Warehouse, Linux, Heroku, Mixpanel, Azure Service Fabric, Apache Kafka, AWS IoT
Storage
Neo4j, PostgreSQL, Data Pipelines, Docker Cloud, Graph Databases, MySQL, Data Integration, Google Cloud, MongoDB, Data Lake Design, Data Lakes, Cloud Environments, OLTP, Redshift, Database Replication, SQL Server DBA, SQL Server Integration Services (SSIS), Azure Cosmos DB, Amazon S3 (AWS S3), Vertica, Google Cloud Storage, Database Administration (DBA), Database Performance, Microsoft SQL Server, Databases, Database Migration, Database Architecture, Cloud Firestore, JSON
Frameworks
Spark, Apache Spark, Scrapy, Selenium
Other
Data Analytics, Data Visualization, ETL Tools, Google Data Studio, Google Cloud Functions, Data Engineering, Google BigQuery, Data Warehousing, Dashboards, Data Analysis, Google SEO, Technical Project Management, Data Warehouse Design, Data Build Tool (dbt), SAP, Data Modeling, Back-end Development, APIs, Parquet, Looker Studio, API Integration, English, Query Optimization, Debugging, IT Support, Data Migration, Data Transformation, Sales, ChatGPT API, Technical Leadership, Google Search Console, SEO Tools, Analytics, Ad-hoc Reporting, Amazon RDS, DAX, Real Estate, Pub/Sub, Performance Tuning, Data-level Security, Machine Learning, Full-stack, Scalability, Startups, Google Tag Manager, Marketing Reports, Data Reporting, Fivetran, Big Data, AWS Cloud Architecture, Data Warehouse Testing, Optical Character Recognition (OCR), Data Science, Web Development, Google Analytics 4 (GA4), Google Pub/Sub, Streaming Data, Google Container Engine, HubSpot CRM, AWR, Designing for Data, Azure Databricks, Azure Data Factory (ADF), eCommerce, Google Cloud Dataflow, Web Analytics, Social Media Web Traffic, Digital Marketing, Database Analytics, Data Processing, Unstructured Data Analysis, Dashboard Development, Reporting, Data Architecture, Sharding, Architecture, Back-end, Cloud Infrastructure, Data Structures, Advisory, Consulting, ELT, Infrastructure, Data, Data Flows, Business Intelligence (BI) Platforms, Marketing Analytics, Amazon Neptune, Data Processing Automation, Metadata, Marketing Strategy, Marketing Campaigns, Marketing Technology (MarTech), TikTok, Causal Inference, Apache Superset, Reports, Analytical Dashboards, Dashboard Design, Database Schema Design, Data Cleansing, ETL Development, Power BI Developer, Cloud Functions & Cloud Scheduler, Stored Procedures & Pub/Sub, Microsoft Azure, Pipelines
Collaboration That Works
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
Share your needs
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
Choose your talent
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
Start your risk-free talent trial
Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.
Top talent is in high demand.
Start hiring