Lead-Data Engineer_VP

Position: Lead-Data Engineer_VP-I
Location: Bengaluru

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.

KEY RESPONSIBILITIES OF

THE ROLE

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.
Internal Process
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

MINIMUM REQUIREMENTS OF KNOWLEDGE & SKILLS
Educational
Qualifications
Bachelor’s or Master’s degree in engineering, Computer Science, or related field
Experience Range (Years and Core Experience Type)
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.
Certifications
NA/ Good to have
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