Docker
Edward K. Ifezulike
Data Engineer
Toronto,ON (Willing to Relocate)
Summary
Results-focused data professional with almost a decade of experience in data transformation and cloud migration using Microsoft Azure and AWS. Expertise in designing, developing and maintaining complex data architecture migration projects and optimizing complex data pipelines and ETL processes. Strong in SQL, Python, and cloud platforms, ensuring seamless data integration and robust data solutions. Known for excelling in collaborative environments, adapting swiftly to evolving needs, and driving team success.
Overview
8
8
years of professional experience
5
5
Certifications
4
4
End-to-end Data Migration Projects Concluded
Work History
Senior Data Engineer
InTouchCX Inc
Winnipeg, Canada
08.2024 - 01.2025
- Built end to end data pipelines, developed modular SQL transformations and created automated testing framework in dbt integrated with CI/CD workflows which improved code reusability while reducing data quality issues by 50%.
- Implemented data pipelines and ETL processes using PySpark, improving overall system efficiency.
- Managed and optimized data warehousing using Snowflake in Azure cloud platform, leading to increased efficiency and data retrieval speed.
- Led the integration of Snowflake into our Azure-based tech stack, improving overall system performance and scalability.
- Exported user lists from legacy system and imported them into Azure Databricks using the admin console ensuring users and roles have appropriate access in the new environment.
- Conducted Engineered enterprise-scale Snowflake data warehouse solution, reducing query processing time by 65% and storage costs by 40% through advanced multi-cluster warehouse optimization and intelligent data partitioning strategies.
- Provided assess code complexity using ETL jobs, PySpark and stored procedures while also defining clear objectives such as scalability, cost reduction and real-time analytics for migration. This ensured a 100% comprehensive migration plan with cost estimates, timelines and resource requirements was created.
- Initiated the mapping of roles and permissions to align with the company policies leading to seamless user access with consistent governance across the platform.
- Implemented advanced SQL query optimization techniques in Snowflake, achieving 80% improvement in complex analytical query performance through materialized views and intelligent caching strategies.
- Successfully utilized Data Modeling techniques to develop and implement scalable Azure-based solutions for complex business challenges.
Lead Data Engineer (Business Development)
United Bank for Africa (UBA GROUP)
Lagos, Nigeria
03.2023 - 07.2024
- Established strong working relationships with stakeholders across multiple departments, facilitating clear communication channels regarding project requirements and progress updates.
- Reinstalled libraries automatically using PySpark (Python Index) repository and copying cluster initialization scripts to the new environment using DBFS CLI ensuring the continuity of analytical workflows with minimal disruption and improving data accuracy to 99% across financial reporting systems.
- Refactored existing Apache Spark, PySpark and SQL based ETL jobs to run on Databricks clusters. This ensured the 100% adoption of ETL workflows in Azure Databricks for data processing.
- Adopted Azure Data Factory to ingest data into Data Lake storage maintaining 100% integrity when moving datasets from the Bank's legacy systems to Azure Databricks.
- Implemented dbt models for transforming raw customer data which reduced query processing time by 45% through optimized transformations.
- Performed bulk data transfers in volumes exceeding 20TB based on business requirements while validating the transferred data using file-by-file validation techniques. This led to a 99% accuracy and completion of the migration process of the datasets to cloud storage.
• Led cross-functional data engineering team in delivering microservices-based data platform using Snowflake and dbt, enabling 40% faster time-to-market for data products. - Used Delta Live tables for building reliable ETL pipelines with enhanced performance while testing sample datasets for full-scale execution resulting in a 100% optimization of fully operational ETL pipelines for cloud performance.
- Exported notebooks as DBC files from the legacy system and import them into Azure Databricks which led to the 100% preservation of existing analytical workflows and custom logic during migration.
- Streamlined data ingestion processes to accommodate increasing volumes of incoming information while maintaining data integrity and ensuring timely accessibility across the organization.
- Delivered high-quality code reviews for colleagues'' contributions following established coding standards and best practices, maintaining consistency throughout projects.
ETL Developer
Access Bank Plc
Lagos, Nigeria
09.2018 - 02.2023
- Enhanced ETL processes by optimizing complex SQL queries and streamlining data extraction procedures.
- Adopted Developed robust Python-based ELT pipelines using Snowflake, PySpark, dbt, and Apache Airflow, successfully migrating 500+ TB of complex multi-source data with 99.98% data integrity and reducing data transformation time by 70%.
- Engineered end-to-end ML data pipelines using Snowflake, Databricks, and Python, facilitating automated feature engineering workflows that reduced data preparation time by 75%.
- Initiated the setup of monitoring dashboards in Azure Monitor and Databricks Workflows for real-time insights into system health ensuring 100% reliability and performance of the migrated system in production.
- Utilized Tableau, Python, and Power BI to develop interactive dashboards and reports, effectively visualizing key performance indicators and delivering actionable insights to stakeholders, reducing report preparation time by 30%.
- Initiated the comparison of results between the legacy system and Azure Databricks for parity leading to the 100% verification and accuracy of migrated data and functionality of workflows.
- Optimized resource allocation using auto-scaling features to reduce costs during peak/off-peak hours while implementing centralized governance unity catalog for consistent security policies across datasets improving efficiency by 80% and reducing costs by 35%.
Data Analyst
Federal Government College
09.2016 - 09.2018
- Produced monthly reports using advanced Excel spreadsheet functions.
- Utilized data visualization tools to effectively communicate business insights.
- Created various Excel documents to assist with pulling metrics data and presenting information to stakeholders for concise explanations of best placement for needed resources.
- Improved decision-making processes with accurate data analysis and visualization techniques.
- Leveraged SQL-based data queries; PowerBI and Looker to improve reporting and analysis, reducing processing time.
- Utilized Tableau, Python, and Power BI to develop interactive dashboards and reports, effectively visualizing key performance indicators and delivering actionable insights to stakeholders, reducing report preparation time by 30%.
- Implemented data security measures in Power BI, ensuring compliance with industry standards and improving data governance quality standards, which contributed to a successful audit with zero security-related findings.
- Part of the team that developed a robust Enterprise Learning Management dashboard that monitors all academic assessments and grades of the school, which improved the learning experience for students.
- Initiated the mapping of roles and permissions to align with the company policies leading to a seamless user access with consistent governance across the platform.
Education
B.Sc. (Hons) - Computer Science
Babcock University
08.2016
Skills
- Stakeholder Engagement
- Git version control
- ETL Process Development
- Technical Solution Design
- Team Collaboration
- BI, ERP & Big Data Platforms
- Data Migration
- Time Management & Prioritization
- MS SQL & Database Management
- User Acceptance Testing
- Requirements Gathering
- Agile Methodologies: Scrum, Kanban
- Leadership Capabilities
- ERP System Configuration
- EPM tools (OneStream, Anaplan)
- Quality Control & Testing
- Cloud & MLOps: AWS, Docker, Git, MLflow
- Data Processing: SQL, Pandas, NumPy
- SAS programming
- Python programming
- Kafka streaming
- NoSQL databases
- Data pipeline design
- Performance tuning
- Hadoop ecosystem
- Data warehousing
- Spark development
- Advanced SQL
- Scala programming
- Java development
- Continuous integration
- Data integration
Certification
- Microsoft Certified Data Engineer Associate - DP203
- Microsoft Power BI Data Analyst Associate - PL300
- CompTIA Data+ Certified
- AWS Certified Solutions Architect - Associate
- Enterprise Design Thinking Practitioner
Projecthighlights
- Loan Eligibility Prediction Project using Python and ML algorithm on GCP @ UBA Group, Part of the team that worked on a loan eligibility prediction project using machine learning on GCP and data visualization with PowerBI to produce actionable insight., The system analyzes historical loan data and bank rules to make accurate eligibility predictions, helping the Bank make data-driven decisions while reducing default risks., The system was deployed on GCP using Vertex AI for scalability and maintainability. During my employment with the Bank, I was part of the team monitoring the model and setting relevant updates to maintain prediction accuracy database using SQL.
- Topic modelling using Kmeans clustering to group customer reviews @ Access Bank Plc, Part of the team that updated the Bank's Virtual Banking chatbot using topic modelling in order to group customer reviews based on recurring patterns., I was able to group customer reviews into distinct topics using Python, identify key themes and patterns in customer feedback and generate actionable insights from review clusters using Python.
- Concept to Clinic (AI for Lung Cancer Detection), 08/01/17, 01/31/19, Part of the team of data engineers who designed an intuitive interface for an AI-powered application, migrating the data from on premises infrastructure to Azure cloud enviroment, reducing radiologists' analysis time by 30%, accelerating diagnostic decisions., Enhanced the AI model's accuracy by 15% through advanced preprocessing techniques, enabling more precise detection of high-risk nodules., Integrated diverse CT scan datasets with a global team, increasing the model's capability to analyze over 200,000 scans from multiple sources.
Corecompetenciesandtechnicalskills
- Business Intelligence & Analytics
- Process Automation
- Stakeholder Engagement
- ETL Process Development
- Technical Solution Design
- Team Collaboration
- BI, ERP & Big Data Platforms
- Data Migration
- Time Management & Prioritization
- JIRA
- MS SQL & Database Management
- User Acceptance Testing
- Agile Methodologies: Scrum, JIRA
- Leadership Capabilities
- ERP System Configuration
- EPM tools (OneStream, Anaplan)
- Postman (APIs)
- Quality Control & Testing
- Cloud & MLOps: AWS, Docker, Git, MLflow, ADLS, ADF
- Data Processing: SQL, Pandas, NumPy
Software
Azure Data Lake Storage
Azure Data Factory
Kubernetes
MongoDB
Synapse Analytics
Timeline
Senior Data Engineer
InTouchCX Inc
08.2024 - 01.2025
Lead Data Engineer (Business Development)
United Bank for Africa (UBA GROUP)
03.2023 - 07.2024
ETL Developer
Access Bank Plc
09.2018 - 02.2023
Data Analyst
Federal Government College
09.2016 - 09.2018
B.Sc. (Hons) - Computer Science
Babcock University
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