[Hiring] Automation Test Lead – Data & Platform Engineering @Virtusa

Role Description

This is a remote position.

• 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.

Qualifications

• 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).

Requirements

• API contract testing (PACT).
• Basic UI automation; data mesh/data product exposure.
• Prometheus/Grafana; regulated domain experience (healthcare, life sciences, finance).