Senior Data Engineer - Python/SQL

Hiring : Senior Data Engineer | 6+ Years.

Location : Bangalore.

Role : Senior Data Engineer.

We are looking for a highly skilled Senior Data Engineer with strong expertise in Data Architecture, System Design, Python, and SQL to design, build, and own end-to-end production data pipelines powering analytics and business decision-making.

The ideal candidate should have strong experience in transaction-level data modeling, data quality, auditability, data lineage, and production pipeline ownership, preferably within finance, risk, or compliance data domains.

Key Responsibilities :

- Own data architecture and system design decisions for data pipelines and data models.

- Design and build scalable, production-grade data pipelines end-to-end.

- Design transaction-level fact tables and standard fact/dimension models.

- Implement Bronze/Silver/Gold (Medallion) architecture.

- Build pipelines for finance, risk, or compliance use cases where accuracy and auditability are critical.

- Implement data quality controls, reconciliation, anomaly detection, and audit trails.

- Write complex SQL using CTEs, window functions, CASE logic, COALESCE, NULLIF, and date/timestamp handling.

- Build idempotent data reload patterns and handle late-arriving or corrected records without double-counting.

- Develop and maintain Airflow-style DAGs and cross-pipeline dependencies.

- Build Python-based ETL tooling using Pandas, SQLAlchemy, and database drivers.

- Work with YAML-driven configurations and integrate with APIs where required.

- Own CI/CD processes using Git workflows.

- Document data models, pipeline logic, data lineage, and operational processes.

Must-Have Skills :

- 6+ years of experience in Data Engineering.

- Strong Python + SQL expertise.

- Strong Data Architecture and System Design skills.

- End-to-end production pipeline ownership.

- Expert SQL including Window Functions, CTEs, CASE logic.

- Strong experience with MySQL / PostgreSQL.

- Experience designing Transaction / Fact Tables.

- Strong data quality, reconciliation, auditability, and lineage practices.

- Experience with Airflow or similar orchestration tools.

- Strong data modeling knowledge - Fact/Dimension, Normalization, Medallion Architecture.

Good to Have :

- Finance, Risk, or Compliance data experience.

- Spark / Hive / Hadoop experience.

- YAML-based pipeline configuration.

- CI/CD and Git workflows.

- API integrations.

- Experience with large-scale production data platforms.