Emmanuel Ikhaiduwor, Developer in Montreal, QC, Canada
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Emmanuel Ikhaiduwor

Verified Expert  in Engineering

Data Engineer and Developer

Location
Montreal, QC, Canada
Toptal Member Since
October 4, 2022

Emmanuel is a highly-skilled data engineer with five years of hands-on experience leading big data projects and executing data-driven solutions for challenging business problems. Proficient in Python, SQL, Airflow, Power BI, Looker, GCP, AWS, PySpark, BASH, Terraform, and Git, Emmanuel is a savvy professional knowledgeable in data science, including data modeling, warehousing, and analysis, business intelligence, and agile project management.

Data AnalyticsData WarehousingPythonSQLETLApache AirflowData EngineeringMicrosoft Power BISnowflakePandasREST APIsTerraformDockerPySparkMachine Learning

Portfolio

Grata Inc
Python, Analytics, Data Analytics, Data Visualization, Docker, Django
Meta
Python, Apache Hive, Spark SQL, Presto DB
Unity
Apache Airflow, Docker, Google BigQuery, Google Cloud Platform (GCP)...

Experience

Python - 5 yearsSQL - 5 yearsData Analytics - 5 yearsETL - 5 yearsApache Airflow - 4 yearsData Warehousing - 4 yearsGoogle BigQuery - 3 yearsSnowflake - 2 years

Availability

Part-time

Preferred Environment

Google Cloud Platform (GCP), Microsoft, Apache Airflow, Python, SQL, Snowflake, Looker, Microsoft Power BI

The most amazing...

...thing I've developed is a data integration framework using Python to enable data ingestion from different sources into Snowflake and BigQuery.

Work Experience

Senior Data Engineer

2022 - 2022
Grata Inc
  • Implemented a Django model to persist API calls reducing geo request usage from over 10,000 to 1000 weekly calls.
  • Performed text analysis and created testable modules to parse addresses leading to improved address normalization using Python.
  • Improved observability of API calls and processes by implementing Datadog.
Technologies: Python, Analytics, Data Analytics, Data Visualization, Docker, Django

Data Engineer

2022 - 2022
Meta
  • Delivered machine learning (ML) training data and analytics data to improve video understanding models and insights.
  • Collaborated with project managers and data scientists to build Hive datasets and Unidash dashboards to understand trends in static and video time spent and support long-range infrastructure investments.
  • Developed a reusable migration framework and supporting documentation using Python and Configurator to aid the migration of ad training data to an enhanced privacy secure storage.
  • Created a training data and metadata pipeline using Spark and Dataswarm to enable training of video understanding models with a potential NE gain of 0.03.
Technologies: Python, Apache Hive, Spark SQL, Presto DB

Lead BI Engineer

2020 - 2022
Unity
  • Built a data integration framework to ingest data from Cloud SQL and BigQuery into Snowflake using Airflow, Python, and YAML templates to unify and enable insights across different databases and organizations and reduce development time.
  • Overhauled legacy internal and external reporting analytics pipelines making them efficient and scalable and leading to yearly savings of $14,000.
  • Developed a revenue forecasting app for Unity Ads using Google App Script based on JavaScript with CRUD functionality, logging, and traceability of cross-functional input. It improved the productivity of the cross-functional forecasting team.
  • Built Looker KPI dashboards to monitor the account activity, sales quota attainment, and growth metrics.
  • Automated manual customer support reports by creating scripts to pull data from several APIs to create reports, saving 5+ hours weekly.
  • Led a three-people team to deliver a foundational data warehouse and infrastructure to enable analytics on new products and services.
  • Created a development environment using Docker, enabling developers to test locally and increasing their productivity.
  • Built a Python-based data validation framework to detect and alert data anomalies, leading to proactive resolutions.
  • Performed regular on-call duties and code reviews, maintaining and debugging Spark jobs, Airflow pipelines, GCP Infrastructure, and Imply dashboards.
  • Led technical training sessions for analysts on Git, Looker, Airflow, and ETL best practices.
Technologies: Apache Airflow, Docker, Google BigQuery, Google Cloud Platform (GCP), Data Warehousing, Python, Looker, Snowflake, REST APIs, Google Cloud SQL, Git, Terraform

Business Intelligence Engineer

2017 - 2020
Pratt & Whitney Canada
  • Developed and managed ETL scripts to power analytics and business intelligence tools and implemented and organized processes to ensure the data integrity of databases.
  • Built a rental-demand forecast algorithm using Python to support informed budget planning decisions of over $10 million on asset investment and maintenance.
  • Created a Python-based asset exposure data application to alert internal users for proactive asset deployment to increase service level and eliminate exposure.
  • Developed and deployed business intelligence tools and monitoring dashboards using Python and Microsoft Power BI to drive business decisions and KPI performance.
  • Conducted research to optimize the warehouse location and proposed a solution that increased in-region coverage by 15%.
  • Led and managed multiple business strategies and process automation, saving over 20 hours monthly.
  • Performed data analysis and wrangling using Python, Pandas, NumPy, and Microsoft Power BI to analyze the market landscape accurately.
  • Utilized NLP to automate the multi-label classification of comments to identify root causes leading to two hours saved weekly.
Technologies: Python, SQL, SAP, Visual Basic for Applications (VBA), Microsoft Power BI, Apache Hive

Data Ingestion Framework into Snowflake and BigQuery

Built a data integration framework to ingest data from CloudSQL and BigQuery into Snowflake and vice versa using Airflow, Python, and YAML templates. The user defines the query or table, dependencies, and schedule in a template rendered by a CI/CD pipeline into a Python script to run on Airflow.

Forecasting Automation Application

Developed an app to automate the extraction and aggregation of data used for revenue forecasting using Google App Script and BigQuery. The app enables CRUD functionality, logging, and traceability of input, leading to increased productivity of the cross-functional forecasting team.

Languages

Python, SQL, Snowflake, Visual Basic for Applications (VBA), Bash, YAML, JavaScript

Tools

Apache Airflow, Looker, Microsoft Power BI, Terraform, Spark SQL, Git, MATLAB

Paradigms

ETL, Data Science

Other

Data Warehousing, Data Analytics, Google BigQuery, Data Engineering, AWS Cloud Architecture, Machine Learning, SAP, Data Analysis, Analytics, Data Visualization

Libraries/APIs

Pandas, PySpark, REST APIs

Frameworks

Presto DB, Django

Platforms

Docker, Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft

Storage

Google Cloud SQL, Apache Hive

2015 - 2017

Master's Degree in Aerospace Engineering

Concordia University - Montreal, Canada

2009 - 2013

Bachelor's Degree in Aerospace Engineering

National Aerospace University – Kharkiv Aviation Institute - Kharkov, Ukraine

AUGUST 2021 - PRESENT

Statistics and Data Science

edX

DECEMBER 2020 - PRESENT

Machine Learning with Python: from Linear Models to Deep Learning

edX

APRIL 2020 - PRESENT

CCA Spark and Hadoop Developer

Cloudera

DECEMBER 2019 - DECEMBER 2022

AWS Certified Solutions Architect

Amazon Web Services