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W2 Only | Principal Data QA Engineer / Lead SDET (Databricks, Spark) | Dallas TX/Seattle, WA ONSITE
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Job at a Glance
- Category
- IT Engineer & Developer
- Location
- Seattle, Washington, United States
- Salary
- Check with seller
- Job Type
- Full Time
- Company
- Jobs via Dice
- Status
- Open & Active
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Advent Global Solutions, Inc., is seeking the following. Apply via Dice today!
W2 ONLY #Due to federal compliance requirements, candidates must be authorized to work in the United States without current or future sponsorship. This role may require eligibility for a U.S. government security clearance.
Candidates who require visa sponsorship (e.g., H-1B, OPT, CPT) are not eligible for this position.
#
Databricks Automation Engineer
100% on-site
Seattle is highly preferred
Open to Dallas TX
Duration: 6 months (can extend)
Rate: $52/hr W2
• Define and own cross-team test architecture and frameworks for ETL/ELT, Databricks/Spark, APIs, and UIs that scale across multiple product teams and environments.
• Design and implement comprehensive data validation and data-quality strategies for large-scale telemetry processing (schema validation, row counts, statistical checks, delta comparisons, anomaly detection, drift detection).
• Architect and enforce CI/CD-integrated automated testing pipelines (Azure DevOps / GitHub Actions) supporting pre-deploy gating, contract testing, canary verification, and regression protection.
• Lead synthetic test data generation strategies and robust mocking/stubbing approaches for downstream dependencies; ensure environment-aware and secure test harnesses for sensitive telemetry.
• Drive performance, scalability, and distributed load testing for Spark jobs and supportingmicroservices; quantify bottlenecks and propose system- and code-level remediation.
• Collaborate with data engineering, platform, DevOps, and product leadership to define acceptancecriteria, release quality gates, and automated verification SLAs.
• Implement and maintain observability for test executions; publish automation health metrics (passrates, flakiness, coverage, mean time to detection) and maintain executive-facing dashboards.
• Own test documentation, runbooks, failure triage playbooks, and on-call handover for production incidents related to data correctness and test infrastructure.
• Lead and grow a high-performing QA/test automation capability — hire, coach, establish standards, and promote best practices organization-wide
Must Have Skills:
• 8+ years of professional software engineering and testing experience, including technical ownership of QA/test practices across the SDLC.
• 3+ years leading or mentoring engineering/QA teams in technical areas (Test Lead, Principal QA Engineer, or similar).
• Deep knowledge of data engineering and lakehouse patterns: partitioning strategies, ACID/Delta semantics, schema evolution, delta table optimization, CDC, time-travel, and data lineage; able to design verification approaches for Databricks/Spark/Delta Lake systems.
• Proven experience architecting and building scalable automated test frameworks and embedding them into enterprise CI/CD using Azure DevOps or GitHub Actions.
• Strong software engineering skills with extensive coding experience in Python, Java, or Scala for test development and automation; ability to review and contribute production-grade code.
• Extensive experience testing data pipelines and big-data processing (Databricks, Spark/PySpark, Delta Lake, ADLS Gen2) or equivalent streaming/batch platforms at scale.
W2 ONLY #Due to federal compliance requirements, candidates must be authorized to work in the United States without current or future sponsorship. This role may require eligibility for a U.S. government security clearance.
Candidates who require visa sponsorship (e.g., H-1B, OPT, CPT) are not eligible for this position.
#
Databricks Automation Engineer
100% on-site
Seattle is highly preferred
Open to Dallas TX
Duration: 6 months (can extend)
Rate: $52/hr W2
• Define and own cross-team test architecture and frameworks for ETL/ELT, Databricks/Spark, APIs, and UIs that scale across multiple product teams and environments.
• Design and implement comprehensive data validation and data-quality strategies for large-scale telemetry processing (schema validation, row counts, statistical checks, delta comparisons, anomaly detection, drift detection).
• Architect and enforce CI/CD-integrated automated testing pipelines (Azure DevOps / GitHub Actions) supporting pre-deploy gating, contract testing, canary verification, and regression protection.
• Lead synthetic test data generation strategies and robust mocking/stubbing approaches for downstream dependencies; ensure environment-aware and secure test harnesses for sensitive telemetry.
• Drive performance, scalability, and distributed load testing for Spark jobs and supportingmicroservices; quantify bottlenecks and propose system- and code-level remediation.
• Collaborate with data engineering, platform, DevOps, and product leadership to define acceptancecriteria, release quality gates, and automated verification SLAs.
• Implement and maintain observability for test executions; publish automation health metrics (passrates, flakiness, coverage, mean time to detection) and maintain executive-facing dashboards.
• Own test documentation, runbooks, failure triage playbooks, and on-call handover for production incidents related to data correctness and test infrastructure.
• Lead and grow a high-performing QA/test automation capability — hire, coach, establish standards, and promote best practices organization-wide
Must Have Skills:
• 8+ years of professional software engineering and testing experience, including technical ownership of QA/test practices across the SDLC.
• 3+ years leading or mentoring engineering/QA teams in technical areas (Test Lead, Principal QA Engineer, or similar).
• Deep knowledge of data engineering and lakehouse patterns: partitioning strategies, ACID/Delta semantics, schema evolution, delta table optimization, CDC, time-travel, and data lineage; able to design verification approaches for Databricks/Spark/Delta Lake systems.
• Proven experience architecting and building scalable automated test frameworks and embedding them into enterprise CI/CD using Azure DevOps or GitHub Actions.
• Strong software engineering skills with extensive coding experience in Python, Java, or Scala for test development and automation; ability to review and contribute production-grade code.
• Extensive experience testing data pipelines and big-data processing (Databricks, Spark/PySpark, Delta Lake, ADLS Gen2) or equivalent streaming/batch platforms at scale.
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