Senior Data Engineer

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.

Requirements

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.

Benefits

· 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.