Data engineer with 4+ years of experience designing and building scalable data pipelines, cloud-native data lake architectures and analytics platforms
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Data engineer with 4+ years of experience designing and building scalable data pipelines, cloud-native data lake architectures and analytics platforms using Python, SQL, AWS, and modern data tooling. Experienced in developing end-to-end ETL workflows, orchestrating pipelines with Airflow, modeling analytical datasets, and deploying data applications using FastAPI, DuckDB and Docker. Strong background in data quality, API integrations, dimensional modeling, and transforming complex business requirements into production-ready data solutions.
Technical Operations Lead (2022-2024)
Led development and maintenance of Python-based ETL pipelines ingesting semi-structured publisher and distributor data (JSON, XML, CSV) into structured relational datasets, supporting large-scale database growth and onboarding of new external partners. Developed data validation and quality control frameworks, optimized SQL-based reporting and analytical workflows, and contributed to dimensional data modeling initiatives using star and snowflake schemas to support operational reporting, traffic analytics, and business intelligence initiatives
Technical Operations Analyst (2020-2021)
Developed and optimized Python-based data processing workflows for ingesting, transforming, validating, and integrating external datasets to improve processing efficiency and data reliability. Created complex SQL queries and analytical reports to support operational and business decision-making, and built metadata-driven matching and reconciliation workflows to align external client data with internal systems for catalog analysis and data coverage initiatives.
Bachelor in Mathematics – University of Waterloo (2015– 2018)
