Jobs › Vizient

QA Automation Engineer with Databricks

Vizient · Chicago, IL · $88,900–$155,500 a year · Full time

Posted Oct 1, 2026 · We last checked this listing on Oct 5, 2026

Apply at Vizient

Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a data quality issue you caught that would have caused real business damage.

What they are checking: Impact awareness and the attention to detail data QA requires.

What would you do

A metric in a dashboard doesn't match finance's number. How do you find out which one is right?

What they are checking: Systematic tracing of business rules and aggregations back to source data.

Data engineers keep shipping changes without telling QA. How do you handle it?

What they are checking: Building collaboration and process so testing keeps pace without becoming a gatekeeper fight.

How do you decide which data validations to automate first?

What they are checking: Risk-based prioritization focused on the most business-critical tables and metrics.

About the work

How would you validate a source-to-target transformation in Databricks when the source has millions of rows?

What they are checking: Efficient reconciliation techniques like counts, checksums and sampling instead of row-by-row comparisons.

Walk me through how you'd test an incremental load that handles updates and deletes.

What they are checking: Understanding of change data handling and Delta table behavior, a common source of hidden data errors.

How do you test referential integrity across Delta tables that don't enforce foreign keys?

What they are checking: Writing SQL checks for orphan records and broken relationships in a lakehouse.

How do you integrate data tests into CI/CD so bad data doesn't reach production?

What they are checking: Practical pipeline integration and gating decisions for data quality.

How do you create test data for a pipeline when you can't use real healthcare data?

What they are checking: Building realistic synthetic data that still exercises edge cases safely.

A pipeline job fails halfway and retries. What would you test to make sure the retry didn't duplicate or lose data?

What they are checking: Thinking about idempotency and recovery scenarios, which the posting calls out directly.

Practice this interview out loud.

Offer builds a real interview for this exact role at Vizient from your resume and this job description, asks the questions one at a time, and tells you what landed. The first one is free.

Practice this out loud

The full job description

As published by Vizient.

When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves . We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. Responsibilities: Required Responsibilities • Develop and maintain automated test suites for Databricks jobs, Delta tables, views, data transformations, and ETL pipelines. • Validate metric calculations, business rules, aggregations, derived values, and source-to-target data transformations within Databricks. • Perform source-to-target reconciliation and validate data completeness, accuracy, consistency, timeliness, and referential integrity across systems. • Develop automated tests for full and incremental loads, updates, deletes, retries, exception handling, and recovery scenarios. • Create test data, SQL validation queries, reusable utilities, and reconciliation frameworks to improve testing efficiency and coverage. • Integrate automated data tests into CI/CD pipelines and enhance test automation frameworks and processes. • Perform functional, integration, regression, and end-to-end testing across large-scale data solutions. • Analyze test failures, conduct root cause analysis, document defects, and collaborate with data engineering and platform teams to resolve issues. Preferred Responsibilities • Validate data and integrations involving Stardog, knowledge graph platforms, and other data technologies. • Test knowledge graph structures, ontologies, relationships, mappings, SPARQL queries, data lineage, and provenance. Estimated Hiring Range: At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $88,900.00 to $155,500.00. This position is also incentive eligible. Vizient has a comprehensive benefits plan! Please view our benefits here: http://www.vizientinc.com/about-us/careers Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.

Apply at Vizient