Back
Tier-1 brand plus Mumbai metro increase applicant density despite seniority and niche platform focus.
Financial data reconciliation, audit-grade controls, and domain-driven quality frameworks require industry-specific experience.
Explicit 10+ years, technical stack, and financial-grade data quality requirements create rigid shortlisting filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead development and scaling of data quality services, APIs, and frameworks to ensure accuracy, consistency, and trustworthiness of financial datasets across the enterprise.
Design and implement data quality controls including profiling, validation, reconciliation, and observability integrated with upstream and downstream data platforms.
Drive technical strategy and architectural direction for enterprise-grade data quality platform; mentor engineering teams and optimize high-volume query workloads in Snowflake/MSSQL.
10+ years of backend/data platform engineering experience with strong hands-on development in Python and modern API frameworks like FastAPI.
Proven experience implementing data quality controls across batch and/or streaming pipelines, including reconciliation and audit-grade financial data controls.
Strong experience with Snowflake and/or MSSQL, including performance tuning and high-volume query optimization.
Bachelor’s/Master’s degree in Computer Science, Engineering, or equivalent experience.
Experienced in building scalable data platform services and end-to-end data quality frameworks covering profiling, validation, and reconciliation with operational impact.
Demonstrated ability to architect and mentor teams on data quality platforms integrating metadata-driven, audit-capable systems in a financial or complex data environment.
Familiarity with containerization, CI/CD pipelines, and cloud-native platforms to support scalable enterprise-grade infrastructure.