The **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** , modern **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 Responsibilities** **1. Technical Leadership & Data Architecture** + **ETL & 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 Optimization** + **Oracle 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 & Collaboration** + **Cross-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 Automation** + **DevOps 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 Standards** + **Team 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 & Competencies** **e** **ETL & 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 transformers **Python 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 profiling **Database & 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 / Bitbucket** **Testing & Quality** - Automated data testing, data reconciliation, boundary testing, and regression suites - Code quality tools and security scanners ( **SonarQube, Checkmarx, Snyk** ) **Experience & Leadership Profile** + **Total 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 prospect 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 (https://www.citigroup.com/citi/accessibility/application-accessibility.htm)_ _._ _View Citi's_ _EEO Policy Statement (https://www.citigroup.com/global/eeo-aa-policy)_ _and the_ _Know Your Rights (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)_ _poster._ Citi is an equal opportunity and affirmative action employer. Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity.

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