Jobs › Companies › V4C.ai › Databricks QA Engineer

About this Databricks QA Engineer role at V4C.ai

V4C.ai · Remote · United States

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

Requirements

  • 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

Benefits

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.

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How this QA Engineer salary compares

This role pays $156,000/yr — in line with the typical range for QA Engineer roles.

$90,395 median $135,500 $193,440

Typical range $111,864–$163,613/yr, from 1,609 comparable QA Engineer listings on JobsRadar (pay annualized to USD). See QA Engineer salary insights →

About V4C.ai

v4c.ai helps enterprises modernize data platforms and accelerate AI initiatives with proven expertise in Databricks. From Lakehouse implementation to workflow migration and ML pipelines, we turn complexity into scalable outcomes.

See all jobs at V4C.ai →

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