Data Quality & Test Automation Engineer

Key Responsibilities:

• Test Automation Architecture & Strategy Data pipelines (batch and streaming)
• APIs and backend services
• Data Testing Framework Engineering SQL based assertions and reconciliation
• Schema validation and evolution checks
• Break Systems Proactively (Destructive Testing Mindset) Schema drift and backward incompatibility
• Late arriving data and partial failures
• ETL and Streaming Validation at Scale Row, aggregate, and hash based reconciliation Incremental and backfill validation
• Data Quality & Observability Integration Great Expectations, Soda
• Accuracy, completeness, uniqueness, timeliness
• CI/CD & DataOps Enforcement Pre merge gates and release blockers
• Selective and parallel test execution
• Test Data Management Synthetic data generation Masking and anonymization
• Performance & Reliability Testing Pipeline and query performance benchmarks
• Concurrency and stress testing
• Security & Compliance Validation PII or PHI exposure
• Encryption and access control
• Cross Functional Quality Leadership Work with data engineers, platform teams, and architects to embed quality early
• Challenge poor design decisions that impact reliability
• Incident Analysis & Prevention Analyze production data issues and failure patterns
• Reduce flaky tests and false alarms

**Mandatory Skills:

• Programming & Framework Development
• Data Engineering Ecosystem
• Data Quality & Observability
• Streaming Systems
• CI/CD & DevOps
• Cloud & Infrastructure

Desired Skills:

• Experience with API contract testing and tools like PACT
• Basic UI automation for end to end validation
• Exposure to data mesh or data product architectures
• Experience 5+ years in automation or quality engineering
• 3+ years building frameworks for data platforms at scale**