Job Description:

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 audit ability.
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:

· Competitive salary and performance-based bonuses.

· Comprehensive insurance plans.

· Collaborative and supportive work environment.

· Chance to learn and grow with a talented team.

· A positive and fun work environment.

Senior Data Engineer

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