Pipeline Architecture & Strategy: Architect, build, and optimize high-throughput, fault-tolerant batch and streaming data pipelines capable of handling mission-critical financial transactions and accounting workflows.
Technical Leadership & Delivery: Lead a pod of data engineers, conduct rigorous code reviews, enforce design best practices, and ensure timely delivery aligned with banking release cycles.
Data Quality & Reconciliation: Implement automated data validation, integrity checks, and ledger reconciliation frameworks to adhere to strict banking accuracy standards.
Stakeholder Management: Work closely with delivery heads, enterprise architects, product owners, and risk/compliance officers to translate banking business requirements into scalable technical implementations.
Mandatory Skills & Qualifications
Experience: Minimum 8+ years of hands-on data engineering experience, including at least 2 years in a technical leadership or module lead capacity.
Databricks: Deep expertise in Databricks Lakehouse architecture, Delta Lake features (Time Travel, ACID transactions, vacuuming, compaction), and Unity Catalog governance.
Python & SQL: Strong software engineering fundamentals in Python (OOP, error handling, unit testing) and expert-level SQL (window functions, query tuning, complex aggregations).
ETL & Data Integration: Proven track record designing enterprise-scale ETL pipelines integrating diverse legacy systems, core banking databases, and modern data warehouses.
BFSI Domain Knowledge: Solid familiarity with banking data models (e.g., core transactions, cards, loans, AML, or risk reporting)