Vaidotas is available for hire
Hire VaidotasVaidotas Kanopa
Verified Expert in Engineering
Data Analyst and Developer
Vilnius, Vilnius County, Lithuania
Toptal member since May 26, 2020
Bio
Vaidotas is a data engineer and full-stack developer who builds high-impact solutions that produce measurable results. Examples include an AI-powered, automated customer support system and an end-to-end BI structure for a data-oriented company. He has expertise in statistics and analytics, strong business acumen, and he enjoys solving complex problems. In addition to a master's degree in financial mathematics and statistics, Vaidotas earned first place in the National Mathematical Olympiad.
Portfolio
Verto Commerce, MB
Amazon DynamoDB, Amazon S3 (AWS S3), Amazon Athena, Microsoft Power BI, Python...
kevin.
Snowflake, Python, Apache Airflow, Data Build Tool (dbt), Amazon S3 (AWS S3)...
Logdirect
Data Modeling, Data Analytics, Talend ETL, Jupyter Notebook, Microsoft Excel...
Experience
- Python - 8 years
- ETL - 8 years
- SQL - 7 years
- Data Engineering - 6 years
- Amazon Web Services (AWS) - 4 years
- SQL Server Analysis Services (SSAS) - 4 years
- Microsoft Power BI - 4 years
- OpenCV - 3 years
Availability
Part-time
Preferred Environment
Python, Amazon Web Services (AWS), Microsoft Power BI, Talend ETL, SQL Server Analysis Services (SSAS), SQL Server Integration Services (SSIS), DAX
The most amazing...
...career event was starting my own company, which gave me a vastly different perspective on owning and operating a business.
Work Experience
CTO, Founder
2023 - PRESENT
Verto Commerce, MB
- Developed four subscription-based apps serving thousands of customers, using Vue and Svelte for the front end and AWS services (Lambda and DynamoDB) for a scalable back-end architecture.
- Built a custom data collection and tracking system that ingested all visitor data into Amazon S3, enabling detailed tracking of visitor journeys, click-through rate analysis for funnels, and A/B testing implementation.
- Developed Python scripts to transform raw event data from S3 into analysis-ready tables for Power BI. Those provided detailed insights into visitor behavior and Facebook Ad performance.
- Created Power BI data models and dashboards to analyze funnel performance, ad effectiveness, and key business KPIs, serving as the main source of information when making management decisions.
- Built Power BI tables to track integration and system errors, identifying issues across Stripe, Klaviyo, and other systems to prevent customer chargebacks and improve system reliability.
Technologies: Amazon DynamoDB, Amazon S3 (AWS S3), Amazon Athena, Microsoft Power BI, Python, Vue 3, Quasar, Svelte, Cloudflare, AWS Lambda, Amazon RDS, Stripe API, Facebook API, Facebook Ads, Google Ads, Klaviyo, JavaScript, PostgreSQL, APIs, Analytics, Reporting, HubSpot API, Generative Artificial Intelligence (GenAI), DAX, Dashboards, Artificial Intelligence (AI), TypeScript, Large Language Models (LLMs), API Integration, ChatGPT, Database Management, Data Integration, Reports, Google Sheets, Marketing, Google Analytics, Notion, Web Development, Data Extraction
Data Engineer
2022 - 2023
kevin.
- Designed and implemented foundational data models for a POS system integrated with an open banking solution, which had previously secured $65 million in funding. These models supported critical analytics and scalability for the product’s success.
- Built and optimized tables in Snowflake to support structured data storage, query efficiency, and accessibility for analytics and reporting.
- Developed automated ETL pipelines using Apache Airflow and DBT, managing event-based data ingestion, transformations, and analytical table creation.
- Integrated data quality checks within Airflow using DBT, creating proactive alerts for data discrepancies or unexpected values and enabling issue resolution prior to daily report distribution.
- Partnered with the data analytics team to refine and optimize data tables in Snowflake, ensuring data structure supported Tableau reporting used by top management.
- Helped optimize the overall data ingestion structure from S3 into Snowflake using Apache Airflow.
Technologies: Snowflake, Python, Apache Airflow, Data Build Tool (dbt), Amazon S3 (AWS S3), Analytics, Data Architecture, Reporting, Dashboards, Data Integration, dbt Cloud, Reports, Google Sheets, Data Extraction
Data Analyst | Data Engineer
2018 - 2022
Logdirect
- Co-created an AI-powered customer support system that automatically handled 1,000 to 5,000 requests per day. The production system was implemented using Salesforce Einstein.
- Built an MVP customer message classification long short-term memory networks (LSTM) model with Python Keras and scikit-learn. This proof of concept led to a decision to launch the customer support automation project into production.
- Created a pipeline to extract and transform over one million email messages into a clean and ML-ready dataset using the Python Pandas library and text manipulation techniques.
- Developed and maintained Microsoft SQL Server Analysis Services (MS SSAS) multidimensional cubes that the majority of the company used as the source for business insights and day-to-day analytics.
- Participated in developing and maintaining an Amazon Redshift data warehouse that was used as the primary data source for the whole company.
- Re-developed ETL processes to provide data for day-to-day use and monitoring. This reduced data loading errors by 70% and helped spot and correct countless data inconsistencies.
- Created Power BI reports providing business insights and monitoring, such as payment reports used by the payments team to spot problems in payment flows, GDPR tracking reports, ETL process monitoring, and an automated customer support report.
Technologies: Data Modeling, Data Analytics, Talend ETL, Jupyter Notebook, Microsoft Excel, Business Intelligence (BI), Keras, TensorFlow, Deep Learning, SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), SQL, NumPy, Data Science, Pandas, Python, Machine Learning, Microsoft Power BI, Redshift, Microsoft SQL Server, Talend, Microsoft Data Transformation Services (now SSIS), Salesforce Einstein, Data Engineering, ETL, Data Warehousing, Relational Databases, Amazon Web Services (AWS), Databases, Data Cleansing, API Integration, APIs, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Data, Database Design, Dimensional Modeling, Git, Data Visualization, Scikit-learn, JSON, Data Pipelines, Snowflake, BigQuery, Analytics, Data Architecture, Reporting, Google Cloud, Data Scientist, DAX, Dashboards, Data Integration, Reports, Google Sheets, Marketing, Amazon Redshift, Data Extraction
Full-stack Developer
2017 - 2018
Self-employed
- Developed a custom, end-to-end software solution for detecting visual anomalies, such as residues in wine, shattered glass, and missing labels. The solution had human-level performance and was capable of processing up to 20 evaluations per second.
- Developed OpenCV-based image processing pipelines to extract images from industrial cameras and prepare them for analysis.
- Integrated deep learning Keras models to work alongside hard-coded computer vision techniques. This led to the ability to use deep learning models on specific parts of images and, in turn, increase their effectiveness.
- Built a user interface using the Kivy framework that allowed non-technical personnel to use the software effectively.
- Collaborated with assembly line managers to analyze problematic specifications and create clear requirements for the ML visual inspection solution.
Technologies: PyCharm, Convolutional Neural Networks (CNNs), Image Processing, Jupyter, Jupyter Notebook, Computer Vision, Keras, OpenCV, NumPy, Data Science, Pandas, Python, Machine Learning, Kivy, Git, Reporting, Artificial Intelligence (AI), Reports, Google Sheets
Founder
2015 - 2018
MB Morsas
- Created and optimized Amazon store listings that resulted in taking the best-selling product position in a major Amazon category.
- Developed multiple online stores using WooCommerce and Shopify, each servicing a few thousand customers.
- Built a semiautomatic customer service system that helped increase agent efficiency by 60%.
- Searched for and negotiated with overseas suppliers and ensured high-quality products and on-time delivery of shipments.
- Developed a structured process for media buying on the Facebook Ads platform, which resulted in quick product testing. The data was gathered and combined using Python and Excel.
Technologies: HTML, Landing Page Optimization, Ad Optimization, WooCommerce, PHP, Python, Facebook Ads, Google Ads, Shopify, MySQL, Google Sheets, Marketing, Google Analytics, AWS Lambda, Excel Macros
Data Analyst
2017 - 2017
Self-employed
- Developed Python Pandas-based ETL processes to produce a BI-ready data source by gathering and combining data from the ERP system (MS SQL database) and custom-made reports.
- Created QlikView reports used by the whole sales team and management to track business performance and help make optimal decisions accurately.
- Assisted in analyzing the data in order to optimize manufacturing processes. Analyses ranged from spotting inconsistencies in product recipes to evaluating the performance of sales promotions.
- Developed Tableau reports to help answer business questions and track key KPIs.
Technologies: Excel VBA, Data Analysis, Microsoft Excel, Business Intelligence (BI), SQL, Data Science, Python, Microsoft SQL Server, QlikView, Data Cleansing, Tableau, Data Engineering, Data, Dimensional Modeling, Data Visualization, Analytics, Matplotlib, Reports
Director of Commerce
2016 - 2017
UAB Daivida
- Oversaw the largest client category, retail chains, which accounted for 40% of the company's revenue.
- Negotiated with clients and acquired new ones, notably the largest EU retail chain, which resulted in a 25% YoY revenue increase.
- Initiated a data-driven approach and developed QlikView reports that helped accurately track the sales process.
- Enhanced Excel reports by using VBA to automatically extract and process data from the ERP system (an MS SQL database). This helped save an average of four hours of employee work time per day and reduce the probability of human data-entry errors.
Technologies: Excel VBA, Microsoft Excel, Business Intelligence (BI), SQL, Microsoft SQL Server, QlikView, ETL, Relational Databases, Databases, Data Cleansing, Data Visualization, Google Sheets, Excel Macros, Data Extraction
Purchasing Manager
2015 - 2016
UAB Daivida
- Ensured a smooth and continuous supply of raw materials for the manufacturing process.
- Searched for and negotiated with suppliers, resulting in 10 to 15% cost reductions on major raw materials used.
- Developed an Excel VBA-based semiautomatic inventory tracking and forecasting system that streamlined inventory evaluation and increased accountability. This resulted in a more efficient purchasing process and less time spent on routine tasks.
- Created ETL scripts to extract inventory/purchasing-related information from the ERP system (MS SQL database) and developed QlikView reports that provided a clear picture of the whole purchasing process, e.g., material pricing, demand, and errors.
Technologies: Excel VBA, Microsoft Excel, Business Intelligence (BI), Microsoft SQL Server, QlikView, Excel Macros, Data Extraction
Senior Specialist
2013 - 2015
VĮ "Žemės Ūkio Informacijos ir Kaimo Verslo Centras
- Researched statistical modeling methods, like linear regressions and BLUP, to determine their best application for selective animal breeding. Model building was done using R.
- Co-created Python-based ETLs to extract necessary data from Oracle databases.
- Provided required governmental analytical reports on the agriculture sector and ensured data quality and accuracy.
Technologies: Statistical Modeling, Statistics, R, Microsoft Excel, Business Intelligence (BI), Data Science, Python, Machine Learning, Oracle SQL, ETL, Relational Databases, Databases, Data Cleansing, Oracle, Data Engineering, Data
Experience
Customer and Prospect Email Request AI-based Autoresponder
I developed an AI-based customer and prospect email request classifier using Salesforce Einstein and co-developed an autoresponder in Salesforce to generate responses.
The problem:
Due to the nature of the business, there were a lot of unanswered prospect email requests posing a lost opportunity, and the costs of treating customer requests were generating huge costs.
Project details:
• Aggregated and transformed Salesforce requests into ML-ready datasets
• Provided the POC version using Python and TensorFlow/Keras
• Trained and tuned models on Salesforce Einstein
• Helped develop an adjustable Salesforce interface for the autoresponder
• Implemented reports to track the performance of the system
• Helped steer the project to achieve the most business value
Result:
The system handled 1,000 to 5,000 prospect and customer requests daily, helping the business improve profitability and increase customer satisfaction.
The problem:
Due to the nature of the business, there were a lot of unanswered prospect email requests posing a lost opportunity, and the costs of treating customer requests were generating huge costs.
Project details:
• Aggregated and transformed Salesforce requests into ML-ready datasets
• Provided the POC version using Python and TensorFlow/Keras
• Trained and tuned models on Salesforce Einstein
• Helped develop an adjustable Salesforce interface for the autoresponder
• Implemented reports to track the performance of the system
• Helped steer the project to achieve the most business value
Result:
The system handled 1,000 to 5,000 prospect and customer requests daily, helping the business improve profitability and increase customer satisfaction.
BI Infrastructure Migration
I helped design the underlying architecture and implemented ETL and Microsoft SSAS migration from local data centers to AWS Cloud.
The problem:
Due to increasing data needs, local data centers became too costly and hard to scale.
Project details:
• Helped design and choose the correct infrastructure for BI needs (EC2 and RDS servers)
• Helped design and implement migration steps ensuring continuous, uninterrupted work
• Designed database schemas and implemented BI data migration to Redshift, RDS, and EC2 Microsoft SQL servers
• Created new adapted Talend ETL flows
Result:
All BI infrastructure was migrated to AWS Cloud, improving the cost and speed with virtually no downtime during migration.
The problem:
Due to increasing data needs, local data centers became too costly and hard to scale.
Project details:
• Helped design and choose the correct infrastructure for BI needs (EC2 and RDS servers)
• Helped design and implement migration steps ensuring continuous, uninterrupted work
• Designed database schemas and implemented BI data migration to Redshift, RDS, and EC2 Microsoft SQL servers
• Created new adapted Talend ETL flows
Result:
All BI infrastructure was migrated to AWS Cloud, improving the cost and speed with virtually no downtime during migration.
Data Democratization
I helped design and implement data democratization in the company, aggregating data from data silos into the central data warehouse and developing Power BI dashboards for analytics.
The problem:
Different departments in the company were using their data and analytics solutions, causing data inconsistencies, lack of data sharing, and inefficient analytics.
Project details:
• Aggregated dispersed data sources into a central data warehouse (AWS Redshift and Spectrum)
• Helped develop a structured Power BI dashboarding system
• Converted into Power BI and optimized existing business analytics solutions
• Co-developed new Power BI reports to answer business needs
Result:
Most of the company's data has been stored in the central data warehouse as the source of truth; data analytics needs have been served by systemized Power BI reports.
The problem:
Different departments in the company were using their data and analytics solutions, causing data inconsistencies, lack of data sharing, and inefficient analytics.
Project details:
• Aggregated dispersed data sources into a central data warehouse (AWS Redshift and Spectrum)
• Helped develop a structured Power BI dashboarding system
• Converted into Power BI and optimized existing business analytics solutions
• Co-developed new Power BI reports to answer business needs
Result:
Most of the company's data has been stored in the central data warehouse as the source of truth; data analytics needs have been served by systemized Power BI reports.
Custom Visual Defect Detection App
I developed an app to find defective wine bottles through visual inspection using image transformation and analysis techniques.
The problem:
In many wine manufacturing plants, defect detection is done manually, which has become costly and introduces human errors.
Project details:
• Based the app on Python and the OpenCV library
• Integrated with industrial-grade cameras
• Achieved real-time speed at 20 evaluations per second
• Developed to be adjustable to new products while evaluating defects against reference images
• Utilized a Kivy-based GUI
Result:
The solution had a human-level performance on most wine bottle types and could process up to 20 evaluations per second.
The problem:
In many wine manufacturing plants, defect detection is done manually, which has become costly and introduces human errors.
Project details:
• Based the app on Python and the OpenCV library
• Integrated with industrial-grade cameras
• Achieved real-time speed at 20 evaluations per second
• Developed to be adjustable to new products while evaluating defects against reference images
• Utilized a Kivy-based GUI
Result:
The solution had a human-level performance on most wine bottle types and could process up to 20 evaluations per second.
Classified Ads Website for Local Businesses
A classified ads website for selling and buying local businesses.
The problem:
Available options to sell or buy local businesses were limited and lacked functionality.
Project details:
• Created a fully serverless implementation using AWS services (Lambda, Amazon API Gateway, Amazon Simple Storage Service (S3), DynamoDB) and Cloudflare as a content delivery network (CDN)
• Enabled automatic scaling
• Developed a reactive single-page application (SPA) front-end using Vue.js
• Constructed user authentication using AWS Cognito
Result:
A fully functioning serverless scalable classified ads website for selling and buying local businesses.
The problem:
Available options to sell or buy local businesses were limited and lacked functionality.
Project details:
• Created a fully serverless implementation using AWS services (Lambda, Amazon API Gateway, Amazon Simple Storage Service (S3), DynamoDB) and Cloudflare as a content delivery network (CDN)
• Enabled automatic scaling
• Developed a reactive single-page application (SPA) front-end using Vue.js
• Constructed user authentication using AWS Cognito
Result:
A fully functioning serverless scalable classified ads website for selling and buying local businesses.
eCommerce Store for a Meat Products Manufacturer
I developed a flexible WooCommerce-based eCommerce store for a meat products manufacturer that started a food delivery service.
The problem:
During COVID-19, in the local city of the manufacturer, people were struggling to order food and basic products safely due to restrictions on movement.
Project details:
• Created a fully functioning WooCommerce online store
• Developed flexible and adjustable delivery time constraints
• Built custom pricing settings on internal product parameters
• Handled sales reports generation
Result:
The company had a fully functioning eCommerce store under a week from the idea's inception.
The problem:
During COVID-19, in the local city of the manufacturer, people were struggling to order food and basic products safely due to restrictions on movement.
Project details:
• Created a fully functioning WooCommerce online store
• Developed flexible and adjustable delivery time constraints
• Built custom pricing settings on internal product parameters
• Handled sales reports generation
Result:
The company had a fully functioning eCommerce store under a week from the idea's inception.
Automatic Product Research App
I developed an app that continuously searched for potentially profitable products to launch on the Amazon marketplace by scanning trending products and determining the competition.
The problem:
It was manually challenging to find which products were popular and had little competition on the Amazon marketplace.
Project details:
• Created a Python-based app using the Selenium framework for web scraping
• Used the results from Google Ads and other third-party providers to find trends
• Used the results from Amazon to find competition for products
Result:
The app results led to investing in products that became high sellers across all EU Amazon marketplaces.
The problem:
It was manually challenging to find which products were popular and had little competition on the Amazon marketplace.
Project details:
• Created a Python-based app using the Selenium framework for web scraping
• Used the results from Google Ads and other third-party providers to find trends
• Used the results from Amazon to find competition for products
Result:
The app results led to investing in products that became high sellers across all EU Amazon marketplaces.
Education
2009 - 2013
Master's Degree in Financial Mathematics and Statistics
University of Warwick - United Kingdom
Certifications
SEPTEMBER 2022 - SEPTEMBER 2025
AWS Certified Data Analytics Specialty
AWS
JULY 2022 - JULY 2025
AWS Certified Cloud Practitioner
Amazon Web Services Training and Certification
DECEMBER 2020 - PRESENT
Machine Learning Scientist with Python – Career Track
DataCamp Inc.
JUNE 2020 - PRESENT
Python Programmer Track – Career Track
DataCamp Inc.
MAY 2020 - PRESENT
Data Analyst with SQL Server – Career Track
DataCamp Inc.
NOVEMBER 2018 - PRESENT
Deep Learning
deeplearning.ai | via Coursera
OCTOBER 2018 - PRESENT
Big Data
University of California San Diego | via Coursera
SEPTEMBER 2018 - PRESENT
Machine Learning
University of Washington | via Coursera
Skills
Libraries/APIs
Pandas, Scikit-learn, OpenCV, NumPy, Keras, TensorFlow, HubSpot API, Kivy, Vue, Vue 3, Stripe API, Facebook API, Matplotlib
Tools
Microsoft Power BI, Microsoft Excel, dbt Cloud, Talend ETL, Git, BigQuery, ChatGPT, Google Sheets, Google Analytics, Tableau, PyCharm, Jupyter, Salesforce Einstein, Amazon Cognito, AWS Glue, Amazon Elastic MapReduce (EMR), Amazon Athena, Amazon Redshift Spectrum, Amazon QuickSight, AWS DataSync, Apache Airflow, Notion
Languages
Python, SQL, Snowflake, HTML, Excel VBA, TypeScript, R, C++, PHP, JavaScript
Paradigms
Business Intelligence (BI), ETL, Dimensional Modeling, Database Design
Platforms
Jupyter Notebook, QlikView, WooCommerce, Amazon Web Services (AWS), AWS Lambda, Google Ads, Windows, Talend, Shopify, Oracle, Salesforce, Apache Kafka, Klaviyo
Storage
SQL Server Analysis Services (SSAS), SQL Server Integration Services (SSIS), Redshift, Relational Databases, Databases, Data Pipelines, Data Integration, SQL Server Reporting Services (SSRS), PostgreSQL, Amazon S3 (AWS S3), JSON, Google Cloud, Database Management, Microsoft SQL Server, Oracle SQL, Amazon DynamoDB, MySQL
Industry Expertise
Marketing
Frameworks
Selenium, Quasar, Svelte
Other
Machine Learning, Data Engineering, Data Science, Data Analysis, Data Modeling, Data Warehousing, Data Cleansing, API Integration, Data, Data Visualization, Analytics, Reporting, Dashboards, Reports, Data Extraction, Deep Learning, Convolutional Neural Networks (CNNs), Facebook Ads, Ad Optimization, Landing Page Optimization, Natural Language Processing (NLP), Computer Vision, Image Processing, Data Analytics, Statistics, APIs, Amazon RDS, Generative Pre-trained Transformers (GPT), Data Build Tool (dbt), Data Architecture, Data Scientist, DAX, Artificial Intelligence (AI), Amazon Redshift, Excel Macros, Web Development, Microsoft Data Transformation Services (now SSIS), Statistical Modeling, Cloud, Cloudflare, Amazon API Gateway, Data Warehouse Design, Web Scraping, Amazon Kinesis, AWS Database Migration Service (DMS), Generative Artificial Intelligence (GenAI), Large Language Models (LLMs)
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