Senior Data Quality Analyst

Role Summary :

Own both data quality and business analysis - lead data validation and reconciliation cycles and provide data quality sign-off, while serving as the client-facing BA who elicits requirements, maps current/future-state processes, and defines KPIs and business rules. Guides junior analysts on execution.

Key Responsibilities :

Data Quality

• Develop and execute data validation plans and rule-based data test cases.

• Validate data accuracy, completeness, consistency, and transformation/business logic.

• Ensure data deliverables meet defined quality standards.

• Identify, log, and track data defects/anomalies; re-validate fixes and confirm resolution.

• Lead data validation and reconciliation cycles; provide data quality sign-off for releases and loads.

Business Analysis

• Elicit and document business requirements and functional/data specifications (BRD/FSD).

• Map current-state and future-state processes and data flows.

• Define KPIs, metrics, and business/validation rules.

• Act as the bridge between the client and delivery teams; facilitate workshops and walkthroughs.

• Review and mentor junior analysts on data quality methodology, SQL, and tooling.

Required Skills :

• 2+ years spanning data quality / data analysis and business analysis.

• Strong, hands-on SQL - profiling, querying, and reconciling large datasets.

• Solid grasp of data quality dimensions (accuracy, completeness, consistency, validity, uniqueness, timeliness).

• Core BA skills - requirements elicitation, BRD/FSD documentation, process modelling, gap analysis.

• Proven client-facing communication and stakeholder management; able to present findings and provide sign-off.

• Experience with data quality / ETL / validation tooling (e.g., Informatica DQ etc)

Nice to Have:

• Cloud data platforms (Microsoft Fabric / Snowflake / Databricks).

• Python for data validation automation.

• Data governance / metadata exposure.

• Tools: Jira, Azure DevOps, Visio (or equivalent process-mapping tool).

• Healthcare Domain familiarity.