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Nspired Digital • New Jersey, United States
Role & seniority: QA Data Engineer – BI & Analytics (Contract), mid-to-senior level
Stack/tools: Advanced SQL (joins, CTEs, window functions, performance debugging); ETL/data pipelines; BI validation (Looker, Power BI, Tableau); data warehousing concepts (facts/dimensions, SCDs, star schemas); QA tools (Jira, TestRail/Zephyr); Agile/Scrum
Design and maintain test plans, scenarios, and regression suites for analytics solutions; translate requirements into test cases and define test data needs
Execute hands-on data testing across ETL pipelines, data models, and dashboards; perform end-to-end validation of features and incremental loads
Log defects with reproduction steps, collaborate with BI/Data Engineers to validate fixes, ensure test coverage aligns with business expectations; contribute to QA governance
Advanced SQL mastery (joins, CTEs, window functions, aggregations, performance debugging)
Experience testing data pipelines, transformations, and BI layers
Hands-on validation of dashboards (Looker, Power BI, Tableau)
Knowledge of data warehousing concepts (facts/dimensions, SCDs, star schemas)
Proven test planning, case creation, and regression suite development; Jira/QA tooling; Agile/Scrum
Strong written/verbal communication; detail-oriented; ability to work independently
Experience with modern data stacks (Looker, dbt, BigQuery, Snowflake)
Exposure to Git-bas
Title: Quality Assurance (QA) Data Engineer – BI & Analytics (Contract)
Location: Remote (US-based preferred Open to Offshore)
Engagement: Contract (Full-time or Part-time, negotiable)
Department: Business Intelligence & Data Analytics
About the Role I'm looking for a highly technical QA Data Engineer contractor to place with one of my clients. The person in this role will support modern BI and analytics initiatives. This is not a manual UI testing role. You’ll be validating data pipelines, transformations, semantic models, and dashboards end-to-end, working closely with BI Engineers, Data Engineers, and Product Managers.
The ideal candidate is deeply comfortable with SQL, understands how analytics systems are built, and knows how to design and execute robust test strategies that catch issues before they reach stakeholders.
What You’ll Do
Test Strategy & Planning Design and maintain comprehensive test plans, scenarios, and regression suites for analytics solutions Translate requirements and acceptance criteria into clear, testable cases Define test data needs and success criteria for BI deliverables
Hands-On Data Testing Execute manual testing across ETL pipelines, data models, and dashboards Validate data accuracy and logic using complex SQL queries Perform end-to-end testing of new features, enhancements, and fixes Conduct smoke testing and validate incremental data loads
Defect Management & Collaboration Log high-quality defects with clear reproduction steps and impact analysis Partner with BI and Data Engineers to troubleshoot and validate fixes Ensure test coverage aligns with business and product expectations
Quality Governance Promote best practices for QA in analytics development Contribute QA input to sprint planning and acceptance criteria Recommend improvements to testing processes and frameworks
Required Qualifications
Technical Advanced SQL (joins, CTEs, window functions, aggregations, performance debugging) Experience testing data pipelines, transformations, and BI layers Hands-on validation of dashboards (Looker, Power BI, Tableau, or similar) Strong understanding of data warehousing concepts (facts/dimensions, SCDs, star schemas)
QA Proven experience creating test plans, test cases, and regression suites Familiarity with Jira and QA tools (TestRail, Zephyr, or equivalent) Experience working in Agile/Scrum teams
Professional Strong written and verbal communication Detail-oriented with a data-first mindset Able to work independently and manage multiple test cycles
Nice to Have Experience with modern data stacks (Looker, dbt, BigQuery, Snowflake) Exposure to Git-based workflows and CI/CD Familiarity with data quality tooling (dbt tests, Great Expectations, Soda) Enterprise BI or analytics platform experience
What Success Looks Like High-confidence releases with fewer regressions Early detection of data quality and logic issues Reusable, well-documented test assets Strong collaboration across BI, data, and product teams
👉 To apply: Send your resume and a brief summary of your experience testing analytics or data platforms.