Automation Test Lead – Data & Platform Engineering

About Us At Virtusa, every innovator has the potential to transform and lead in a digital world—but unlocking that potential takes more than technology; it takes a trusted partner who combines engineering excellence, creativity, and an AI-first mindset. Together, we co-create solutions that help businesses grow faster, operate smarter, and make experiences better with technology. Job Description This is a remote position. Responsibilities: Test Automation Architecture & Strategy: Own a scalable, modular, metadata-driven framework covering data pipelines (batch/streaming), APIs/backend services, and end-to-end data product validation; enable plug-and-play components, parallel execution, environment isolation, deterministic runs Data Testing Framework Engineering: SQL-based assertions/reconciliation, schema validation, data contracts, lineage/freshness validation, config-driven test definitions (YAML/JSON) Destructive Testing: Schema drift, backward incompatibility, late-arriving data, partial failures, duplicate/missing/out-of-order events, stress, concurrency, retries, DLQ handling, backpressure ETL/Streaming Validation at Scale: Row/aggregate/hash-based reconciliation, incremental/backfill validation, delivery semantics validation, window/time-based correctness Data Quality & Observability: Integrate/extend Great Expectations or Soda; custom validations for accuracy, completeness, uniqueness, timeliness; quality dashboards CI/CD & DataOps Enforcement: Pre-merge gates, release blockers, selective/parallel test execution, GitHub Actions/Jenkins integration Test Data Management: Synthetic data generation, masking/anonymization, deterministic datasets, edge case simulation Performance & Reliability Testing: Pipeline/query benchmarks, concurrency/stress testing, data skew analysis, cost/time optimization Security & Compliance: PII/PHI exposure checks, encryption/access control, retention, audit requirements; support GxP/SOX/ISO frameworks Cross-Functional Quality Leadership: Work with data engineers, platform teams, architects; mentor engineers Incident Analysis & Prevention: Root-cause analysis of production data issues, reduce flaky tests Requirements Strong Python (test frameworks, libraries, CLI tools); advanced SQL Hands-on DBT, Airflow, Snowflake or similar; ETL/ELT and data modeling Great Expectations/Soda; lineage and catalog systems Kafka/Kinesis testing; delivery semantics Git workflows; CI/CD (Jenkins, GitHub Actions) AWS; IaC (Terraform/CloudFormation) Desired Skills: API contract testing (PACT); basic UI automation; data mesh/data product exposure; Prometheus/Grafana; regulated domain experience (healthcare, life sciences, finance)