Data Analyst

Job Level JL5

Location – Pune, Chennai, Bangalore, Hyderabad, Chandigarh.

Notice period – 0-30 days only

1. Requirements Engineering & Regulatory Translation

Translate Regulatory Text: Analyze and translate complex regulatory rules, methodology documents, and policy updates into clear, unambiguous functional requirements documents (FRDs), business requirements documents (BRDs), data mapping templates, and transformation logic specifications.

Methodology Implementation: Interpret regulatory guidance and Citi’s internal liquidity methodologies, converting them into actionable system requirements for development teams.

Change Management: Manage and assess the impact of change requests driven by evolving regulatory updates, audit findings, or methodological enhancements.
2. Data Analysis, Lineage & Reconciliation

Large-Scale Data Analysis: Query and analyze large, complex datasets across multiple upstream source systems (e.g., deposits, secured funding, derivatives, off-balance sheet products).

Data Lineage & Mapping: Perform end-to-end data lineage analysis from transaction sourcing to final regulatory reporting, ensuring complete transparency and traceability.

Reconciliation & Validation: Reconcile source-to-report figures, validate stress calculations, and perform comprehensive data quality checks.

Issue Triage & Resolution: Lead data analysis and issue triage to resolve breaks, anomalies, and reconciliation gaps across reporting cycles.

Remediation Strategies: Identify systemic data quality issues and define robust remediation strategies in collaboration with data governance and technology teams.
3. Stakeholder Collaboration & Advisory

Cross-Functional Bridge: Act as the primary liaison between Treasury, Liquidity Risk, Methodology, Technology, Data, and QA teams to ensure alignment on project goals and deliverables.

Facilitate Walkthroughs: Lead requirement walkthroughs, impact assessments, and solution design discussions with both technical and non-technical stakeholders.
4. Testing, Quality Assurance & Production Support

Testing & Parallel Runs: Define testing strategies, write test cases, and support User Acceptance Testing (UAT), parallel runs, and production certifications to ensure reporting accuracy and regulatory compliance.

Developer Collaboration: Work daily with developers to clarify data sourcing, transformation rules, and reporting logic, ensuring technical designs align with business intent.

Continuous Improvement: Continuously identify opportunities to improve automation, strengthen data controls, and enhance documentation to support reporting sustainability and auditability.
5. Agile Delivery & SDLC Compliance

Agile Frameworks: Work within Agile or hybrid SDLC models, actively participating in backlog refinement, sprint planning, daily stand-ups, and retrospective sessions.

System Dependencies: Maintain a strong understanding of upstream/downstream system dependencies, batch processing schedules, and reporting timelines to ensure seamless delivery.

Qualifications & Experience

Required Experience

Education: Bachelor’s / Master’s degree in Finance, Economics, Computer Science, Management Information Systems (MIS), or a related quantitative field.

Professional Experience: 5–8+ years of experience as a Business Analyst, Functional Analyst, or Data Analyst within a global financial institution, consulting firm, or financial technology provider.

Domain Expertise: Strong understanding of Treasury, Liquidity Risk Management, and regulatory reporting frameworks. Direct experience with FR 2052a, ILST, LCR (Liquidity Coverage Ratio), NSFR (Net Stable Funding Ratio), or Reso is highly preferred.

SDLC Methodologies: Proven experience working within Agile (Scrum/Kanban) or hybrid SDLC frameworks, including using tools like Jira and Confluence.
Technical Skills & Competencies

Data Querying: Advanced SQL skills are required to query databases, analyze data structures, and perform data profiling.

Data Mapping: Strong expertise in creating source-to-target data mappings, data dictionaries, and transformation logic.

Analytical Tools: Advanced proficiency in Microsoft Excel (VLOOKUPs, pivot tables, complex formulas) for data reconciliation and prototyping.

Data Lineage: Familiarity with data lineage concepts, metadata management, and data quality frameworks.

Programming/BI (Preferred): Exposure to Python, R, or Business Intelligence tools (e.g., Tableau, Power BI) is a plus.
Soft Skills

Communication: Exceptional verbal and written communication skills, with the ability to explain complex financial calculations and technical data flows to diverse audiences.

Problem Solving: Strong analytical and problem-solving skills, with a meticulous attention to detail and a track record of resolving complex data anomalies.

Collaboration: Proven ability to build relationships and collaborate effectively across cross-functional, global teams.

Resilience: Ability to thrive in a fast-paced, deadline-driven environment with evolving regulatory priorities.

Role & responsibilities

Preferred candidate profile