Job Description
đ Hiring: Senior Data Engineer | 6+ Years
Location: Bangalore
Experience: 6+ Years
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.
đ ď¸ Must-Have Skills
â 6+ years of experience in Data Engineering
â Strong Python + SQL expertise
â Strong Data Architecture and System Design skills
â End-to-end production pipeline ownership
â Expert SQL including Window Functions, CTEs, CASE logic
â Strong experience with MySQL / PostgreSQL
â Experience designing Transaction / Fact Tables
â Strong data quality, reconciliation, auditability, and lineage practices
â Experience with Airflow or similar orchestration tools
â Strong data modeling knowledge â Fact/Dimension, Normalization, Medallion Architecture
â 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