Data Quality & Test Automation Engineer (Senior)

DecisionPoint | Cortek • Chicago, IL

8d • Remote

About The Position

DecisionPoint seeks a Senior Data Quality & Test Automation Engineer to independently validate data pipelines, schemas, calculations, datasets, and reporting outputs supporting the USMEPCOM ENLIST program’s AI integration and data analysis activities. The engineer will develop SQL reconciliation tests, automated regression checks, access tests, and data freshness and performance tests. The role verifies that data remains accurate, complete, consistent, appropriately accessible, and traceable as it moves from source systems through transformations, warehouses, analytical models, dashboards, and reports.

The engineer will work with data engineers, AI/ML engineers, business analysts, developers, cybersecurity personnel, and Government stakeholders to identify defects, document evidence, verify corrections, and provide independent assessments of data and reporting quality. The position is remote, with Chicago-area candidates preferred. Applicants acknowledge that their resumes may be included in an active competitive government contract bid.

Requirements

• Active Secret clearance or higher.
• Minimum of eight years of relevant professional experience.
• Bachelor’s degree in computer science, information systems, data analytics, or a related field, or a permitted equivalent.
• Experience developing and executing SQL reconciliation tests.
• Experience validating data pipelines.
• Experience developing or maintaining automated regression tests.
• Experience performing access testing.
• Experience implementing or validating data-quality controls.
• Ability to independently validate schemas, calculations, datasets, and reporting outputs.
• Ability to develop and execute data freshness and performance tests.
• Ability to maintain test evidence, defect records, dataset checks, and retest results.
• CompTIA Security+ CE or another approved IAT Level II certification when applicable to assigned duties.

Nice To Haves

• ISTQB test automation certification or Certified Data Management Professional (CDMP) certification.
• Experience supporting federal or Department of Defense data, analytics, or software programs.
• Experience testing data warehouses, ETL/ELT processes, data integrations, or analytical platforms.
• Experience validating Power BI or comparable dashboards, semantic models, calculated measures, and self-service reports.
• Experience with Python or another scripting language used for data testing and automation.
• Experience integrating automated tests into CI/CD pipelines.
• Familiarity with data lineage, metadata management, data governance, and controlled test environments.
• Experience validating datasets used by AI or machine learning systems.
• Strong analytical troubleshooting, technical documentation, and cross-team communication skills.

Responsibilities

• Independently validate data pipelines, schemas, transformation logic, calculations, datasets, and reporting outputs against documented requirements and business rules.
• Develop SQL reconciliation tests comparing source data with intermediate datasets, warehouse tables, analytical outputs, dashboards, and reports.
• Verify record counts, totals, aggregations, joins, mappings, calculated fields, and source-to-target completeness.
• Test data schemas, field types, required values, relationships, referential integrity, and handling of schema changes.
• Build automated regression checks to detect unintended changes following pipeline, schema, calculation, application, or reporting updates.
• Validate data-quality controls for accuracy, completeness, consistency, uniqueness, validity, and timeliness.
• Develop access tests to verify authorized access, role restrictions, data visibility, and expected behavior for unauthorized users.
• Test data freshness, refresh schedules, processing latency, pipeline execution times, and reporting performance.
• Validate error handling for missing, duplicate, malformed, late-arriving, or otherwise invalid data.
• Maintain repeatable test datasets, expected results, reconciliation rules, and automated dataset checks.
• Verify that training, validation, testing, and analytical datasets meet documented quality and preparation requirements.
• Maintain traceability among requirements, business rules, test cases, test data, execution results, defects, and retest evidence.
• Integrate automated data-quality and regression checks into approved delivery pipelines and scheduled validation processes.
• Document test procedures, execution results, supporting queries, discrepancies, and reproducible evidence.
• Record and track defects, coordinate investigation with responsible teams, and verify corrections through retesting.
• Assess the effect of data or calculation defects on downstream models, dashboards, reports, and mission decisions.
• Support user acceptance testing by preparing validated datasets, reconciling expected results, and investigating reported discrepancies.
• Provide test status, defect trends, unresolved risks, and release-readiness findings to technical teams and Government stakeholders.
• Maintain test documentation, defect records, dataset checks, and retest results for program reviews and inspections.
• Improve test coverage and automation based on recurring defects, production findings, and lessons learned.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior