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Sr Lead DQA-Databricks-Snowflake
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Job Description
Job Requirements
About the Role
Virtusa is seeking an elite Data Quality Assurance (DQA) Engineering Lead and Subject Matter Expert (SME) to spearhead the technical execution of a massive Data Quality Center of Excellence (CoE) for a leading healthcare payer.
Databricks & Snowflake DQA Architecture
Platform SME: Serve as the foremost technical authority on executing scalable data quality frameworks within Databricks (PySpark, Delta Lake) and Snowflake (Snowpark, Dynamic Tables).
Shift-Left Automation: Architect and implement Data Quality as Code (DQxC) strategies that embed validation checks, schema enforcement, and anomaly detection directly into data ingestion and transformation pipelines.
CI/CD Pipeline Integration
Framework Development: Build, maintain, and scale centralized, reusable DQ code libraries and templates that standardize how engineering Pods execute data quality checks.
Code Reviews & Standards: Conduct rigorous code reviews for data quality implementations, ensuring performance optimization and adherence to architectural best practices.
Generative AI & Advanced Automation
Experience & Technical Expertise
10+ Years of Experience: Extensive background in Data Engineering, Data Architecture, or highly technical Data Quality Engineering.
Databricks SME (Required): Deep, hands-on expertise in Databricks, including PySpark, Spark SQL, Delta Lake architecture, and performance tuning for large-scale data processing.
Snowflake SME (Highly Preferred): Strong experience with Snowflake architecture, Snowpark (Python), task scheduling, and data sharing.
Programming & Scripting: Advanced proficiency in Python, PySpark, and SQL. You must be a coder who treats data quality as a software engineering discipline.
Shift-Left & DQxC: Proven experience building programmatic data quality frameworks (e.g., Great Expectations, dbt tests, Soda, or bespoke PySpark/Python frameworks) from the ground up.
AI & Automation Acumen
Preferred Qualifications
Healthcare Payer Domain: Understanding of healthcare payer data ecosystems (Medicare, Medicaid, Claims processing, HL7/FHIR, and PHI/PII compliance).
Platform Certifications: Active Databricks Certified Data Engineer Professional and/or SnowPro Advanced: Data Engineer certifications.
Agile/Pod Delivery: Experience operating as a technical lead in a scaled Agile (SAFe) or Pod-based delivery model
Work Experience
7-10Years
About the Role
Virtusa is seeking an elite Data Quality Assurance (DQA) Engineering Lead and Subject Matter Expert (SME) to spearhead the technical execution of a massive Data Quality Center of Excellence (CoE) for a leading healthcare payer.
Databricks & Snowflake DQA Architecture
Platform SME: Serve as the foremost technical authority on executing scalable data quality frameworks within Databricks (PySpark, Delta Lake) and Snowflake (Snowpark, Dynamic Tables).
Shift-Left Automation: Architect and implement Data Quality as Code (DQxC) strategies that embed validation checks, schema enforcement, and anomaly detection directly into data ingestion and transformation pipelines.
CI/CD Pipeline Integration
Framework Development: Build, maintain, and scale centralized, reusable DQ code libraries and templates that standardize how engineering Pods execute data quality checks.
Code Reviews & Standards: Conduct rigorous code reviews for data quality implementations, ensuring performance optimization and adherence to architectural best practices.
Generative AI & Advanced Automation
Experience & Technical Expertise
10+ Years of Experience: Extensive background in Data Engineering, Data Architecture, or highly technical Data Quality Engineering.
Databricks SME (Required): Deep, hands-on expertise in Databricks, including PySpark, Spark SQL, Delta Lake architecture, and performance tuning for large-scale data processing.
Snowflake SME (Highly Preferred): Strong experience with Snowflake architecture, Snowpark (Python), task scheduling, and data sharing.
Programming & Scripting: Advanced proficiency in Python, PySpark, and SQL. You must be a coder who treats data quality as a software engineering discipline.
Shift-Left & DQxC: Proven experience building programmatic data quality frameworks (e.g., Great Expectations, dbt tests, Soda, or bespoke PySpark/Python frameworks) from the ground up.
AI & Automation Acumen
Preferred Qualifications
Healthcare Payer Domain: Understanding of healthcare payer data ecosystems (Medicare, Medicaid, Claims processing, HL7/FHIR, and PHI/PII compliance).
Platform Certifications: Active Databricks Certified Data Engineer Professional and/or SnowPro Advanced: Data Engineer certifications.
Agile/Pod Delivery: Experience operating as a technical lead in a scaled Agile (SAFe) or Pod-based delivery model
Work Experience
7-10Years
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