Data-ETL Engineering Lead-Vice President

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 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 . View Citi’s EEO Policy Statement and the Know Your Rights poster.