Lead Data Analyst - MDM

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.

Position Title: Lead Data Analyst – Enterprise Data & Analytics

Career Level: P3

Job Category: Manager

Role Type: Hybrid

Job Location: Bangalore

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.

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:

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

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

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

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

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

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

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

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 tasks

Basic understanding of Master Data Management concepts — what MDM is, why golden records matter, and how data flows between systems

Awareness of how downstream systems (Snowflake, reporting tools, UI applications) consume MDM data

Exposure to Informatica Customer 360 / Reference 360 is a plus, but not required

Accuracy and completeness of data validation outputs and reconciliation documentation

Quality of defect logs — clear, reproducible, and fully evidenced

Timely escalation of data issues and discrepancies to P4 leads

Reliable completion of assigned UAT test cases within sprint or release timelines

Growing confidence and independence in SQL-based validation and data analysis tasks over time

Positive feedback from Senior Leads on quality of support and documentation

Primary Focus: Data validation, reconciliation support, and requirements documentation across MDM consumption workstreams

Analyst — Not Developer: Interprets, documents, and validates data flows — does not build pipelines or write production code

Key Strength: Attention to detail + growing MDM data knowledge + structured documentation and communication

Supports: MDM Team, Senior, Juniors MDM Analysts and Product Lead across all consumption, Data Quality, Remediation and reporting workstreams

Reports to: Senior MDM Lead / Data Management Leadership

Partners: Data Engineering, Operational/Reporting Teams, Data Stewards, Business Stakeholders, Senior leaders and cross-functional teams.

We are committed to providing an inclusive and accessible hiring process. If you require accommodations at any stage (e.g. application, interviews, onboarding) please let us know, and we will work with you to ensure a seamless experience.

FC Global Services India LLP (First Citizens India) is an Equal Employment Opportunity Employer. We are committed to fostering an inclusive and accessible environment and prohibit all forms of discrimination on the basis of gender, religion, caste, disability, sexual orientation, economic status or any other characteristics protected by the law. We strive to foster a safe and respectful environment in which all individuals are treated with respect and dignity. Our EEO policy ensures fairness throughout the employee life cycle.