Databricks QA Engineer

About the role

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.

Posting text as published by V4C.ai.

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United States

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