Lead Data Analyst - MDM

FC Global Services India LLP (First Citizens India), a part of First Citizens BancShares, Inc., a top 20 U.S. financial institution, is a global capability center (GCC) based in Bengaluru. Our India-based teams benefit from the company’s over 125-year legacy of strength and stability. First Citizens India is responsible for delivering value and managing risks for our lines of business. We are particularly proud of our strong, relationship-driven culture and our long-term approach, which are deeply ingrained in our talented workforce. This is evident across all key areas of our operations, including Technology, Enterprise Operations, Finance, Cybersecurity, Risk Management, and Credit Administration. We are seeking talented individuals to join us in our mission of providing solutions fit for our clients’ greatest ambitions.

Job Description:

Value Preposition:

Shaping the Future of Enterprise Master Data Management within Enterprise Data & Analytics. Lead and strengthen MDM data consumption, quality, validation, and downstream reporting processes. Drive data integrity across Customer 360 / Reference 360 ecosystems while enabling high-quality, governed, and analytics-ready data for enterprise and regulatory consumption.

Contribute to the evolution of data culture by building and enhancing data infrastructure, reporting frameworks, optimizing data pipelines, Data remediation for Regulatory Reporting needs and mentoring teams on data storytelling and visualization best practices with advanced data technologies and experience.

Job Details

Position Title: Lead Data Analyst – Enterprise Data & Analytics

Career Level: P3

Job Category: Manager

Role Type: Hybrid

Job Location: Bangalore

About the Team:

This role operates within the MDM Data Management – Customer 360 / Reference 360 Programme , supporting enterprise-wide data consumption and downstream reporting. The team ensures that MDM golden records are accurately propagated across APIs, batch pipelines, Snowflake, and reporting layers.

The Lead Analyst plays a critical role in bridging data producers and consumers , ensuring that MDM data is reliable, well-documented, and aligned with business and regulatory expectations. Working collaboratively with cross-functional pod members, the Business Analyst will drive efficient workflows, optimize data systems, and support iterative delivery in a fast-paced Agile environment.

Impact:

The P3 Junior MDM Analyst supports the analysis, validation, and documentation activities required to ensure that data flowing from MDM 360 (Customer 360 / Reference 360) into downstream systems is accurate, consistent, and fit for purposes.

This is an analyst — not a developer — role. Rather than building pipelines or writing production code, the Junior MDM Analyst interprets data flows, documents findings, validates data quality, supports requirements gathering, and assists with UAT and reconciliation reviews across consumption and reporting workstreams.

This role is an excellent entry point into MDM programme delivery, offering exposure to:

MDM 360 → APIs / Batch → Snowflake → Financial Reporting → UI Consumption

Key Deliverables (Duties & Responsibilities):

1. MDM Data Understanding & Documentation

Develop a working understanding of MDM golden record structures and how data flows from MDM 360 to downstream systems

Document data flows, field mappings, and transformation logic under the guidance of the P4 Analyst or BA Lead

Maintain and update data mapping registers, attribute lists, and business rule logs as requirements evolve

Assist in maintaining the MDM data dictionary — recording field definitions, data types, and ownership

Note and escalate data anomalies or gaps in documentation identified during analysis activities

2. Data Validation & Quality Checking

Supporting validation across the consumption data flow — from MDM through to reporting:

Run and review data validation checks across:

MDM golden records vs. API payload outputs

Batch pipeline outputs vs. expected source data

Snowflake consumption layer vs. MDM source records

UI-displayed data vs. MDM and Snowflake outputs

Use SQL (with guidance) to query datasets, identify discrepancies, and validate attribute-level accuracy

Apply data quality checks across key dimensions — completeness, accuracy, consistency — and document outcomes

Log and track data quality issues in agreed tooling (e.g. JIRA, SharePoint, Excel trackers)

Escalate unresolved or high-impact data discrepancies to the P4 Analyst or BA Lead promptly

3. Downstream Reporting & Financial Data Support

Support validation of MDM data used in financial and regulatory reporting layers

Assist in reconciliation activities between:

MDM golden records and Snowflake reporting datasets

Reporting output and expected business values for key financial attributes and hierarchies

Document reconciliation results clearly — noting matched records, mismatches, and volumes

Assist in investigating data breaks and reporting discrepancies by gathering relevant data and preparing findings for P4 review

Track and follow up on outstanding reconciliation items through to resolution

4. Requirements Support & Analysis Documentation

Supporting the P4 BA in translating business needs into clear, documented requirements:

Attend requirements workshops, take structured notes, and circulate agreed actions and decisions

Assist in drafting user stories, acceptance criteria, and data mapping specifications under senior guidance

Review and cross-check requirements documents for completeness, consistency, and alignment with MDM data standards

Maintain up-to-date requirements logs and traceability matrices for the consumption workstream

Raise questions and clarification points with the P4 Analyst when requirements are unclear or ambiguous

5. API & Batch Pipeline Validation Support

From an analysis — not development — standpoint:

Review API payload structures (JSON) and validate that field mappings match agreed data specifications

Use API testing tools (Postman, Swagger) under guidance to inspect responses and document findings

Monitor batch job outcomes and validate data completeness and successful execution against expected results

Log pipeline validation findings and assist in drafting defect descriptions for technical teams

Track open pipeline issues through to resolution, providing status updates to the P4 lead

6. UAT Support & Defect Tracking

Support UAT activities across API, batch, Snowflake, and reporting validation scenarios

Execute test cases defined by the P4 Analyst or BA Lead — validate data movement accuracy and business rule adherence

Log defects clearly and completely in agreed defect tracking tools — including steps to reproduce, observed vs. expected results, and data evidence

Track defects through to resolution and retest fixes as required

Assist in preparing UAT summary notes and test evidence for sign-off activities

Skills and Experience :

Analytical Skills

Strong attention to detail — able to spot discrepancies in data across multiple systems

Structured thinking and ability to organise findings clearly in written form

Comfortable working with large datasets and identifying patterns, gaps, or anomalies

Ability to ask the right questions and escalate issues appropriately

Data & Technical Acumen

Intermediate SQL — able to write and run queries for data validation, comparison, and reconciliation (joins, filters, aggregations)

Familiarity to some expertise in API concepts (REST/JSON) — able to read and interpret payloads with guidance

Basic exposure to Snowflake or similar cloud data platforms (querying and exploring data)

Understanding of data quality concepts — completeness, accuracy, consistency, and timeliness

Comfortable using tools such as Excel, JIRA, Confluence, Postman, or Swagger for analysis and tracking