Discover your future at CitiWorking at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.Job OverviewThe Data & ETL Engineering Lead (C13) is a senior technical leadership role responsible for architecting, designing, and delivering enterprise-scale data integration, ETL/ELT pipelines, and data warehousing solutions. This role requires an expert data engineer with deep hands-on proficiency in Ab Initio, up-to-date Python-based data engineering, and relational database engines (Oracle DB).As a C13 Data Lead, you will oversee end-to-end data delivery across the Software Development Life Cycle (SDLC), collaborate closely with cross-functional business and technical stakeholders, define data architecture and modeling standards, and implement automated CI/CD deployment pipelines for high-throughput batch and real-time processing systems.Key Responsibilities1. Technical Leadership & Data ArchitectureETL & Pipeline Architecture: Lead the architecture, design, and implementation of robust, high-volume batch and real-time ETL/ELT pipelines using Ab Initio and Python.Data Warehousing Design: Define and implement dimensional data models (Star Schema, Snowflake Schema, Slowly Changing Dimensions - SCD Type 1/2/3/4/6, Conformed Dimensions, Fact Tables) supporting large-scale enterprise reporting and analytics.Data Governance & Quality: Enforce enterprise data governance standards, data lineage, metadata management, data dictionary maintenance, and automated data validation/reconciliation frameworks.2. Database Engineering & Performance OptimizationOracle Database Development: Lead database design, complex SQL authoring, and advanced PL/SQL programming (Stored Procedures, Packages, Triggers, Table Functions).Performance Tuning: Perform comprehensive performance tuning of large-scale ETL graphs, Python jobs, and Oracle queries via execution plans, indexing strategies, table partitioning, parallel execution, and optimizer hints.Volume Management: Architect solutions capable of processing multi-terabyte datasets within stringent SLA time windows.3. Stakeholder Management & CollaborationCross-Functional Partnership: Act as the primary technical liaison between business stakeholders, data product owners, quantitative analysts, reporting teams, and enterprise infrastructure partners.Requirements Translation: Translate complex business rules and regulatory requirements into detailed technical specifications, source-to-target mappings (STTM),



and data flow architectures.Agile & Program Delivery: Partner with Scrum Masters and Project Managers to plan sprint roadmaps, estimate technical effort, mitigate data pipeline risks, and manage dependency handoffs.4. CI/CD & DevOps AutomationDevOps for Data Pipelines: Build and standardize automated CI/CD pipelines for packaging, testing, and deploying Ab Initio code/graphs, Python scripts, and Oracle DDL/DML migrations (e.G., using Jenkins, Harness, Tekton, GitLab CI, Liquibase).Version Control & Release Management: Manage code repositories, branching workflows, and configuration management across environments (Dev, SIT, UAT, Prod).Operational Monitoring & Production Resilience: Establish monitoring and alerting systems (e.G., Autosys, Control-M, Grafana, Splunk, Loki), lead Root Cause Analysis (RCA) for critical batch failures, and drive operational stability.5. Team Mentorship & Engineering StandardsTeam Leadership: Mentor and guide mid-level and junior ETL developers, data analysts, and database engineers.Standardization: Establish code review checklists, design patterns, reusable ETL modules/subgraphs, and automated unit/regression testing standards across data engineering teams.Technical Skills & CompetencieseETL & Data Integration
- Deep hands-on expertise in Ab Initio (Co> Operating System, GDE, Enterprise Meta> Environment (EME), Continuous Flows, Plan> It, Express>It, Component Development, Subgraphs, Partitioning/De-partitioning)
- Strong experience building custom data extractors, loaders, and transformersPython Data Engineering
- Advanced Python 3.X for data processing and pipeline scripting
- Proficiency with libraries such as Pandas, NumPy, PyArrow, SQLAlchemy, PySpark, Polars
- Writing clean, object-oriented, testable Python code with unit test coverage (pytest/unittest)Data Warehousing & Modeling
- Comprehensive understanding of Data Warehousing & Data Lakehouse concepts (Inmon vs. Kimball methodologies)
- Dimensional modeling (Star / Snowflake schemas, Factless Facts, Aggregate tables, SCD Types)
- Data lineage, Source-to-Target Mappings (STTM), metadata governance, and data profilingDatabase & SQL
- Advanced Oracle 19c+ & PL/SQL programming (Complex joins, window functions, analytical functions, CTEs)




- Deep knowledge of Oracle optimizer, query execution plans, indexes (B-tree, Bitmap), partitioning/sub-partitioning strategies, and bulk operations (FORALL, BULK COLLECT)CI/CD & Infrastructure
- Experience in CI/CD pipeline authoring (Jenkins, Harness, Tekton, GitHub Actions, GitLab CI)
- Database change management tools (e.G., Liquibase, Flyway)
- Linux/Unix shell scripting (Bash/Ksh), job scheduling tools (Autosys, Control-M, Airflow)
- Version control with Git / BitbucketTesting & Quality
- Automated data testing, data reconciliation, boundary testing, and regression suites
- Code quality tools and security scanners (SonarQube, Checkmarx, Snyk)Experience & Leadership ProfileTotal Experience: 10+ years of professional experience in data engineering, data warehousing, and ETL development, with at least 3+ years leading technical teams or complex data engineering initiatives.Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Software Engineering, Data Analytics, or equivalent quantitative discipline.Domain Knowledge: Prior experience in banking, financial services (e.G., Risk, Regulatory Reporting, Capital Markets, Retail Banking, Wealth Management), or large enterprise data systems is highly preferred.Communication & Influence: Proven ability to communicate effectively with business stakeholders, summarize complex technical data architectures, and lead discussions with senior leadership.------------------------------------------------------Job Family Group: Technology------------------------------------------------------Job Family:Applications Development------------------------------------------------------Time Type:Full time------------------------------------------------------Most Relevant Skills Please see the requirements listed above.------------------------------------------------------Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi (opens in new window).View Citi’s EEO Policy Statement (opens in new window) and the Know Your Rights (opens in new window) poster.

📌 Data-Etl Engineering Lead-Vice President (Pune)
🏢 Citigroup
📍 Pune