Description

We are seeking a hands on QA Lead to drive quality assurance for a scalable, enterprise-wide data platform for an insurance client. The role involves validating batch and real-time data pipelines, ensuring data accuracy across Raw, Silver, and Gold layers, and supporting report rationalization and self-service analytics (Power BI).

The QA Lead will define and implement end-to-end data testing strategies, covering ingestion (AWS Glue, Kinesis), transformation (DBT), and consumption layers, while ensuring data quality, integrity, and performance optimization.

Key Responsibilities

1. QA Strategy & Leadership

- Define and implement end-to-end QA strategy for the enterprise data platform
- Establish test frameworks, standards, and governance for data validation
- Lead QA planning, estimation, and execution across multiple data streams

2. Data Validation & Testing

- Validate data across Raw, Silver, and Gold layers ensuring accuracy, completeness, and consistency
- Perform source-to-target reconciliation for batch and real-time pipelines
- Design and execute:
- Data quality checks
- Transformation validation (DBT models)
- Aggregation and KPI validation

3. Batch & Real-Time Pipeline Testing

- Test batch ingestion pipelines using AWS Glue
- Validate real-time streaming data pipelines using Amazon Kinesis
- Ensure data latency, sequencing, and event consistency in streaming pipelines

4. Reporting & Rationalization QA

- Validate datasets powering Power BI self-service reports
- Support report rationalization initiatives by ensuring consistency of KPIs and eliminating redundant data sources
- Perform report/data reconciliation testing across legacy vs new platform

5. Automation & Tools

- Develop and implement automated data testing frameworks
- Leverage SQL, Python, and testing tools (e.g., Excellent Expectations, DBT tests, custom frameworks)
- Enable continuous testing integration within CI/CD pipelines

6. Performance & Optimization Testing

- Validate performance of:
- Data pipelines




- Queries in Snowflake

- Identify bottlenecks and work with engineering teams to optimize pipelines and queries
- Ensure scalability for large data volumes and concurrent workloads

7. Data Quality & Governance

- Define and enforce data quality rules, thresholds, and monitoring
- Implement data anomaly detection and alerting mechanisms
- Ensure compliance with audit, reconciliation, and governance standards

Required Skills & Experience

Core Technical Skills

- Strong experience in data testing / ETL testing / data QA
- Hands-on expertise with:
- Snowflake (data validation, SQL testing)
- DBT (testing, model validation)
- AWS Glue (batch pipeline validation)
- Amazon Kinesis (real-time pipeline testing)

- Advanced proficiency in SQL for data validation and reconciliation
- Programming skills in Python (preferred)

Testing Expertise

- Experience in:
- Data reconciliation (source vs target)
- Data quality frameworks and validation techniques
- Automated data testing tools

- Understanding of medallion architecture (Raw, Silver, Gold layers)

Analytics & Reporting

- Experience validating Power BI reports and datasets
- Strong understanding of business KPIs and reporting consistency

Domain Expertise (Preferred)

- Experience in Insurance domain (Policy, Claims, Billing data)
- Familiarity with regulatory reporting, audit, and reconciliation requirements

Experience

- 8–12 years in QA / Data Testing / ETL Testing
- 3+ years in QA leadership or lead role
- Experience working on enterprise-scale data platforms

Responsibilities

Domain Expertise (Preferred)

- Experience in Insurance domain (Policy, Claims, Billing data)
- Familiarity with regulatory reporting, audit, and reconciliation requirements

Experience

- 8–12 years in QA / Data Testing / ETL Testing
- 3+ years in QA leadership or lead role
- Experience working on enterprise-scale data platforms

Qualifications

Experience

- 8–12 years in QA / Data Testing / ETL Testing
- 3+ years in QA leadership or lead role
- Experience working on enterprise-scale data platforms

📌 DE&A -Data Engineer ETL Developer (Snowflake) (Pune)
🏢 Zensar Technologies
📍 Pune