Databricks QA Engineer

V4C.ai · Remoto · USA Only

Recebendo candidaturas · conferida em 14/11

Exige residência em Estados Unidos

Ficha da vaga

Modelo
Remoto
Onde aceita
Exige residência em Estados Unidos
Senioridade
Senioridade não informada
Salário
$70 – $80 per hour

Fonte: We Work Remotely · Ver vaga original →

  • python
  • sql
  • ci cd

Organizei a descrição em seções com IA. O texto completo da vaga está logo abaixo.

Sobre a vaga

V4C.ai is seeking a Databricks QA Engineer to own test strategy, release sign-off, and automated test suites in Python and PySpark for enterprise data platforms.

O que você vai fazer

  • Own test strategy and release sign-off on engagements, including documented test plans covering scope, risk, and coverage
  • Build and maintain automated test suites in Python and PySpark (pytest), integrated into CI pipelines
  • Validate data pipelines end to end: ingestion, Medallion layer transformations, Delta Lake tables, and ELT workflows
  • Implement data quality rules as code, including Lakeflow expectations and reusable validation frameworks
  • Run regression validation after code changes and maintain CI quality gates that block merge or promotion on failure

O que pedem

  • 5+ years in QA automation or test engineering, including meaningful time testing data pipelines rather than applications alone
  • A data engineering background: you can read a pipeline, reason about a transformation, and write the SQL to verify it
  • Expert-level SQL
  • Experience with Medallion architecture, Delta Lake, and ELT-based data platforms
  • Experience building automated suites that run in CI and gate deployment

Descrição completa da vaga

Headquarters: United States

URL: https://jobs.workable.com/company/kb5Wja5n4RGDc2pq5FujAz/jobs-at-v4c.ai

About V4C V4C is a pure-play Databricks partner, and in under two years we have earned 850+ Databricks certifications across 325+ customers and been named Databricks' 2026 Partner of the Year (C&SI Emerging). As a Databricks QA Engineer on our data engineering team you will own the quality gate for enterprise data platforms, working directly with customers. You will work on live enterprise data platforms alongside one of the most heavily Databricks-certified delivery teams in the market.

The Role This is a QA role for people who understand data engineering, not general software QA pointed at a data project. You will validate Lakehouse pipelines, which means reasoning about row counts, schema drift, late-arriving data, and silent transformation errors no UI will ever surface. Our approach is automation-first: suites in Python and PySpark, running in CI, blocking promotion when they fail. You own release sign-off, which makes you the last person between a customer and bad data in production. Responsibilities Own test strategy and release sign-off on engagements, including documented test plans covering scope, risk, and coverage Build and maintain automated test suites in Python and PySpark (pytest), integrated into CI pipelines Validate data pipelines end to end: ingestion, Medallion layer transformations, Delta Lake tables, and ELT workflows Implement data quality rules as code, including Lakeflow expectations and reusable validation frameworks Run regression validation after code changes and maintain CI quality gates that block merge or promotion on failure Partner with engineers to identify automation candidates and raise the coverage bar across the practice

5+ years in QA automation or test engineering, including meaningful time testing data pipelines rather than applications alone A data engineering background: you can read a pipeline, reason about a transformation, and write the SQL to verify it Expert-level SQL Experience with Medallion architecture, Delta Lake, and ELT-based data platforms Experience building automated suites that run in CI and gate deployment Demonstrable hands-on experience working on Databricks or similar platforms

Preferences Healthcare or life sciences experience preferred but not required Existing Databricks certification(s) Hands-on experience with Unity Catalog, Lakeflow pipelines, or Databricks Asset Bundles Experience with Azure DevOps pipelines, or equivalent CI tooling (GitHub Actions, GitLab CI) Familiarity with contract-based data validation standards such as ODCS Experience using LLM agents or MCP-connected tooling to run validations, triage failures, or draft defect reports Consulting or client-facing background

Pay Rate: $70 – $80 per hour (1099 independent contractor). This is a contract engagement rather than a salaried employee role. Where a rate lands within the range depends on depth of data-pipeline testing experience and automation capability. Open to contractors anywhere in the United States.

To apply: https://weworkremotely.com/remote-jobs/v4c-ai-databricks-qa-engineer

Perguntas e respostas sobre a vaga

Aceita candidatos de onde?
Exige residência em Estados Unidos.
Qual o regime de contratação?
A vaga não diz.
É remota?
Sim, é remota.
Informa salário?
Sim: $70 – $80 per hour.

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