Senior Data Engineer | 6+ Years

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.

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