Databricks QA Engineer

V4C.ai; United States; Remote; USD 96,000 - 110,000; Part time

Job summary

V4C is seeking a QA Engineer focused on data engineering to own the quality gate for enterprise data platforms. You will validate Lakehouse pipelines, implement data quality as code, and maintain automated tests in Python and PySpark within CI pipelines.

You will work with a highly certified Databricks delivery team, review end-to-end pipelines, and drive release sign-off to prevent bad data from reaching customers.

Qualifications

• 5+ years in QA automation or test engineering, including data pipelines.
• A data engineering background: you can read a pipeline and verify transformations with SQL.
• Expert-level SQL and hands-on Databricks experience are required.
• Experience with Medallion architecture, Delta Lake, and ELT-based data platforms.
• Experience building automated suites that run in CI and gate deployment.
• Hands-on experience with Databricks or similar platforms.

Responsibilities

• Own test strategy and release sign-off on engagements with documented test plans.
• Build and maintain automated test suites in Python and PySpark (pytest) in CI.
• Validate end-to-end data pipelines: ingestion, Medallion layers, Delta Lake, ELT workflows.
• Implement data quality rules as code and reusable validation frameworks.
• Run regression validation after code changes and maintain CI quality gates.
• Collaborate with engineers to raise coverage and quality across the practice.

Skills

QA automation

SQL

Python

PySpark

CI/CD

Databricks

Tools

Delta Lake

Lakeflow

Unity Catalog

Azure DevOps

GitHub Actions

Job description

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.