Data Quality Engineer - Assistant Vice President

The Data Quality Engineer is a critical role to the design, build, and maintenance of the data quality (DQ) infrastructure that underpins Legal’s regulatory reporting, governance, analytics, and AI‑enablement objectives. This role blends technical engineering, data quality management, and platform expertise, ensuring Legal’s most critical data assets are accurate, reliable, and fully compliant with Citi policies—including EUC/ITESS requirements.

The ideal candidate has strong hands‑on proficiency with Dataiku, Python, and dashboarding frameworks, and is comfortable collaborating across Legal, EDO, GFT, CTI, Data Risk & Controls, and Reporting & Analytics. This role drives the buildout and continuous enhancement of Legal’s DQ environment, including SDLC modernization, integration with enterprise tooling, and development of scalable monitoring and exception‑management capabilities.

Responsibilities Data Quality Engineering & Pipeline Development Build and maintain DQ pipelines in Dataiku using visual recipes, code recipes (Python), and automation frameworks. Enhance and refactor existing solutions to support environment‑agnostic SDLC operation, ensuring portability across development, QA, UAT, and production environments.

Implement scalable code components for profiling, threshold checks, rule execution, and exception handling. Partner with Tech (GFT, CTI) to design and deploy changes aligned to enterprise engineering standards. DQ Rule, Exception & Issue Lifecycle Support Translate DQ requirements into executable rule logic; implement thresholds, severity tiers, and alerting.

Maintain exceptions and concerns workflows, including automated monitoring, status updates, and reporting. Support LGRU DQRE initiatives (Phase 1, Phase 2) including user training, lessons learned, and post–go‑live enhancements. Integration with EDO Tooling & Enterprise Controls Lead technical work to maintain integration of Legal’s DQ platform with EDO‑approved tools.

Support Legal’s DQ platform as ITESS – including documentation, compliance with Citi ITESS SDLC and release requirements, dependencies, and control adherence. Metrics, Dashboards & Monitoring Develop and maintain highly interactive dashboards (e.g., MetricsOne, R&C Dashboard, Jira Scrum Dashboard, OKR Dashboard) using Dataiku Webapps, Python (Flask, Dash), and web technologies (HTML/CSS/JS).

Automate data ingestion where possible; monitor data integrity and troubleshoot input issues. Partner with Reporting & Analytics and Data Strategy to ensure dashboards align with enterprise design and visualization standards. New Initiatives & AI Innovation Support Identify automation opportunities and propose new DQ engineering solutions, AI‑enabled data quality prototypes, and enhancements to monitoring architecture.

Participate in feasibility assessments, solution design, and stakeholder presentations for innovation‑focused initiatives. Project & Stakeholder Management Provide structured, proactive communication with DQ teams, domain owners, Tech partners, and reporting stakeholders.

Maintain project plans, RAID logs, documentation packets, and release readiness materials across DQ projects like SDLC upgrades, EDO integrations, and dashboard rebuilds. Qualifications Technical Skills Dataiku (strong proficiency): visual and code recipes, model deployment, orchestration, Webapps, plugin integration.

Familiarity with Python for data pipelines, API integrations, automation, and dashboard backend components. Familiarity with HTML/CSS/JavaScript for dashboard UX/UI improvements. Experience with SDLC, Git, promotion through environments, automated testing, and CI/CD principles.

Data Quality & Controls Strong working knowledge of DQ dimensions, rule design, exception workflows, and data validation patterns. Understanding of EUC/ITESS control requirements and experience documenting technical applications for compliance.

Familiarity with metadata/lineage concepts and integration with enterprise data governance tools. General Qualifications Relevant experience in data engineering, data quality, or analytics engineering roles. Strong technical communication skills—able to translate complex issues for non‑technical stakeholders.

Ability to manage multiple initiatives simultaneously, balancing delivery pressure with engineering discipline. Experience within financial services or other highly regulated environments strongly preferred. Education Bachelor’s degree required; Master’s degree preferred in Computer Science, Data Engineering, Information Systems, or related technical field. ------------------------------------------------------ Job Family Group: Data Governance ------------------------------------------------------ Job Family: Data Governance Foundation ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Data Governance, Data Management, Data Quality, Internal Controls, Management Reporting, Policy, Procedure, and Regulation, Program Management, Risk Controls and Monitors. ------------------------------------------------------ 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.

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