Lead-Data Engineer (VP)

Job description

JOB DESCRIPTION: • The Lead-Data Engineer will be responsible for architecting, building, and governing enterprise-scale data pipelines and platforms for Ujjivan Small Finance Bank. The role ensures secure, high-quality, reliable, and timely data availability to support analytics, regulatory reporting, risk management, and AI/ML initiatives. • This role provides technical and people leadership, defines data engineering standards, and acts as a key interface between business, analytics, governance, and technology teams. • Design and own end-to-end data pipeline architecture across batch and near real-time processing aligned to enterprise strategy. • Define and govern bronze, silver, and gold data layer architecture for enterprise consumption. • Enable analytics, ML, and AI use cases by delivering model-ready and feature-ready datasets that drive business outcomes. • Optimize data pipeline performance and cost efficiency. • Establish CI/CD pipelines for data engineering, including version control, testing, and controlled deployments. • Contribute to planning, budgeting, and prioritization of data engineering initiatives aligned to business goals. • Collaborate with business, analytics, and risk teams to translate requirements into scalable data solutions. • Lead ingestion of data from Core Banking, LOS, LMS, Collections, CRM, Payments, Finance, and external data sources to support internal and external consumers. • Enable timely, reliable, and high-quality data availability for stakeholders across the organization. • Partner with Data Quality & Governance teams to operationalize Critical Data Elements (CDEs), lineage, and metadata for stakeholder trust and usability. • Ensure pipeline scalability, fault tolerance, restart ability, and SLA adherence. • Implement workflow orchestration, dependency management, backfills, and automated retries. • Embed automated data quality checks, reconciliation controls, and anomaly detection. • Ensure secure data handling, including masking, encryption, and role-based access control. • Ensure compliance with regulatory, audit, and information security requirements. • Comply with internal SLAs, policies, and standard operating procedures. • Drive process management and continuous process excellence across data engineering workflows DESIRED CANDIDATE PROFILE: Educational Qualifications • Bachelor’s or Master’s degree in engineering, Computer Science, or related field Experience Range • 12-15 years of experience in data engineering or large-scale data platform development. • Proven experience in banking or financial services data environments. • Demonstrated experience leading teams and enterprise data programs. Functional Skills • Advanced SQL and strong programming skills in Python / Scala and pyspark. • Deep understanding of Cloud architecture and Devops • Strong experience with ETL/ELT frameworks and distributed data processing. • Hands-on experience with data orchestration and scheduling frameworks. • Deep understanding of data warehousing, data lakes, and layered data architectures. • Expertise in data quality, reconciliation, metadata management, and data lineage. • Strong knowledge of CI/CD, version control (Git), and automated testing for data pipelines. • Experience with data security, masking, encryption, and role-based access control. • Exposure to streaming or near real-time data processing is desirable. • Understanding of ML/AI data requirements and feature engineering pipelines