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. (ref:hirist.tech)