Automation Test Lead – Data & Platform Engineering

Job not on LinkedIn

🔥 14 hours ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🏗️ Platform Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Virtusa

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1996

💼 Consulting

🏢 Enterprise

🤖 Artificial Intelligence

💰 $108M Post-IPO Equity - Virtusa on 2017-05

Consulting • Enterprise • Artificial Intelligence

Virtusa is a global technology services and consulting company that helps enterprises reimagine their business through digital engineering, AI-driven and domain-focused solutions. It offers consulting, design, engineering, automation, analytics and optimization services, and partners with organizations across banking & financial services, communications, healthcare, insurance, retail, manufacturing and other industries to deliver enterprise-scale technology and AI solutions. Virtusa emphasizes AI services, domain-driven solutions for the AI enterprise, and end-to-end digital transformation.

📋 Description

• Own a scalable, modular, metadata-driven test automation framework covering batch and streaming data pipelines, APIs/backend services, and end-to-end data product validation • Enable plug-and-play components, parallel execution, environment isolation, and deterministic test runs • Engineer SQL-based assertions and reconciliation, schema validation, data contracts, lineage/freshness validation, and YAML/JSON config-driven test definitions • Test schema drift, backward incompatibility, late-arriving data, partial failures, duplicate/missing/out-of-order events, stress, concurrency, retries, DLQ handling, and backpressure • Validate ETL/streaming at scale through row, aggregate, and hash-based reconciliation; incremental/backfill validation; delivery semantics; and window/time-based correctness • Integrate or extend Great Expectations or Soda and build custom data-quality validations and dashboards • Enforce CI/CD and DataOps through pre-merge gates, release blockers, selective/parallel execution, and GitHub Actions/Jenkins integration • Manage test data through synthetic generation, masking/anonymization, deterministic datasets, and edge-case simulation • Conduct pipeline/query benchmarks, concurrency/stress testing, data-skew analysis, and cost/time optimization • Perform PII/PHI exposure checks, encryption/access-control validation, retention and audit checks, and support GxP/SOX/ISO frameworks • Work with data engineers, platform teams, and architects; mentor engineers • Perform root-cause analysis of production data issues and 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 experience • Experience with Great Expectations/Soda • Experience with lineage and catalog systems • Kafka/Kinesis testing experience • Knowledge of delivery semantics • Git workflows • CI/CD with Jenkins or GitHub Actions • AWS experience • Infrastructure as code with Terraform or CloudFormation • 9+ years in automation/QE • 5+ years building frameworks for data platforms at scale • Track record improving reliability and reducing incidents • API contract testing (PACT) desired • Basic UI automation desired • Data mesh/data product exposure desired • Prometheus/Grafana experience desired • Regulated domain experience in healthcare, life sciences, or finance desired