DQA Analyst Agile (Hyderabad)

• DQA Analyst Agile (Hyderabad)
• Company: Virtusa
• Job Location: Hyderabad, Telangana, India
• Employment Type: Full-time
• Experience Required: 7 - 10 years
• Job Requirements

Virtusa is seeking a highly experienced Senior Data Quality Assurance (DQA) Analyst to act as the vital bridge between business stakeholders and data engineering Pods for a premier healthcare payer clients Data Quality Center of Excellence (CoE). As the requirements anchor for your Agile Pod, you will own the end-to-end lifecycle of Data Quality Requirements.

• Responsibilities
• Full-Lifecycle DQ Requirements & Stakeholder Sign-Off
• Ingestion to Consumption Specification:
• Lead the collection, analysis, and detailed specification of data quality requirements across the entire data lifecycle ready for Databricks/Snowflake implementation.
• Azure DevOps (ADO) & Agile Artifact Management
• Epic & User Story Creation:
• Act as the primary author and owner of all Agile artifacts within Azure DevOps. Translate the CoE roadmap and business requirements into well
• structured Epics, Features, User Stories, and granular Tasks.
• Backlog Grooming & Sprint Planning:

Lead backlog refinement sessions with the DQA Engineering Lead and developers, ensuring Acceptance Criteria for every DQ rule are explicitly defined, testable, and strictly adhered to.

• Required Qualifications
• Experience & Domain Expertise
• 10+ Years of
• Experience:
• Extensive background as a Data Analyst, Systems Analyst, Healthcare Payer
• Expertise:
• Deep knowledge of healthcare payer data domains, including Claims processing, Member enrollment, Provider networks, and clinical data compliance.
• Agile / Scrum Mastery: Deep, practical experience operating in Agile delivery models
• Azure DevOps (ADO) Mastery: Proven, hands-on expertise in administering and structuring work within Azure DevOps
• Advanced SQL: Highly proficient in writing complex SQL queries for data profiling, exploration, and validation across relational and cloud databases.
• Data Quality Concepts: Deep understanding of core data quality dimensions
• Preferred Qualifications
• Shift-Left Understanding: Conceptual understanding of CI/CD pipelines and how data quality checks are integrated programmatically into automated data engineering workflows.
• Gen AI Familiarity: Experience using AI tools for business analysis, writing Agile user stories, or metadata harvesting.
• Up-to-date Data Platforms: Familiarity with the concepts of Azure Databricks, Snowflake, and Medallion architecture.
• Work Experience
• 7-10Years .