Senior Data Engineer

Requirements:

• 6+ years of experience in data engineering.
• Strong data architecture and system design skills with the ability to make sound trade-offs around data modeling, partitioning, and scalability.
• Demonstrated end-to-end ownership of production data pipelines, including design, deployment, monitoring, and operational support.
• Expertise in Python and SQL as primary tools; experience with Hive/Hadoop is a plus.
• Strong focus on data quality, validation, reconciliation, anomaly detection, and auditability.
• Experience working with finance, risk, compliance, or other highly regulated data domains requiring strong data lineage and governance.
• Proven experience designing and building transaction and fact tables.
• Advanced SQL skills, including window functions, CTEs, CASE statements, and working across MySQL/PostgreSQL environments.
• Strong Python expertise, including pandas, SQLAlchemy, type hints, data classes, and object-oriented pipeline development.
• Experience with workflow orchestration platforms such as Airflow or similar tools.
• Strong understanding of data modeling concepts including fact/dimension modeling, normalization, and medallion architecture.
• Experience with YAML-based configurations, CI/CD practices, and Git-based development workflows.

Strongly Preferred:

• Experience with enterprise data platforms, internal data tooling ecosystems, metadata/catalog solutions, secrets management tools, developer productivity platforms, and ETL orchestration frameworks.

Nice-to-Have:

• Experience with Hive, Hadoop, Spark, or related big data technologies.

Skills

Airflow, Python, SQL