Website CITI

Data Quality Lead Analyst at Citi (FRMT Data Services)

Citi is a global powerhouse in financial services, and this role within the FRMT (Finance, Risk, and Managed Technology) Data Services platform is a critical leadership position. You will be overseeing a global data repository anchored to Liquidity and Collateral management, ensuring that the data used for Treasury, Finance, and Risk reporting is accurate, compliant, and architecturally sound.

This is a Senior/Lead-level role (8+ years experience) that combines deep technical expertise in Big Data ecosystems with the strategic “big picture” required for Enterprise Data Governance.

🟢 Role Overview & Impact

As a Lead Analyst, you are the technical authority for data integrity. You aren’t just checking boxes; you are designing the frameworks that ensure Citi’s financial and contractual data is “fit for purpose” for regulatory reporting and capital management.

  • Strategy & Governance: Secure approvals from Data Governance Officers and implement “tollgate” documentation to ensure all data scorecards meet global standards.

  • Complex Data Profiling: Build assessments for critical data elements (CDEs) across strategic systems, identifying patterns, trends, and anomalies in massive datasets.

  • Technical Mentorship: Lead and mentor junior analysts while collaborating with Technology teams to implement modern data quality tools.

  • Global Collaboration: Work in a heavily matrixed environment, influencing stakeholders across Finance, Risk, and the Chief Data Office (CDO).

📊 Compensation & Salary Benchmarks (2026)

Based on verified 2026 data for Senior/Lead Data roles at Citi India (Bengaluru/Mumbai/Pune):

Metric Details
Average CTC (8+ Years) ₹28 LPA – ₹42 LPA
Variable Component : Typically includes a 10%–15% performance bonus.
Total Compensation : Top-tier candidates with NoSQL and Python expertise can exceed ₹48 LPA.
Benefits : World-class insurance, global mobility opportunities, and professional certification support.

🎯 Required Tech Stack & Qualifications

  • Experience: 8+ years in IT/Data Analysis with a focus on Financial Services.

  • Big Data & NoSQL: Expert-level knowledge of Cassandra, Hadoop (HBase), and MongoDB.

  • Database Engines: Deep understanding of SQL Server, Oracle, Netezza, and Teradata.

  • Programming: Proficient in Python for developing analytics and automation scripts.

  • Visualization: Ability to build BI views in Tableau or Qlikview.

  • Governance Knowledge: Proven experience in Data Lineage, Data Tracing, and Data Quality frameworks.

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