Senior Data Quality / QA & UAT Lead
Jobgether United States
Internet Marketplace Platforms · 11-50 employees
About the role
The role involves owning the verification framework, testing environments, and data quality controls for an enterprise-ready decision intelligence platform. You will lead UAT activities, manage the defect lifecycle, and provide evidence for formal government validation and milestone approval.
What they look for
Requirements
Candidates must have 8+ years of experience in software QA, data testing, or technical systems validation, specifically within government IT programs. Proficiency in SQL, ETL/ELT pipeline testing, and quantitative quality measurement is required, along with U.S. citizenship or permanent residency.
Benefits
Full description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Quality / QA & UAT Lead based in the United States.
This is a senior technical validation role supporting the transformation of a data analytics proof of concept into an enterprise-ready decision intelligence platform. You will own the verification framework, testing environments, data quality controls, and user acceptance pipelines across a high-visibility government technology program. The role combines hands-on data testing, QA governance, performance validation, defect management, and UAT leadership. You will establish measurable quality thresholds and independently verify that complex data pipelines, business rules, dashboards, and integrations meet contractual requirements. Your work will provide the evidence required for formal government validation, acceptance, and milestone approval. The position is part-time and deliverable-focused, with workload increasing during major acceptance gates, onboarding waves, and platform performance tuning. This opportunity is well suited to an experienced QA or data quality professional who thrives in highly accountable, metrics-driven environments.
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Accountabilities
- Build and maintain the master integrated verification matrix, ensuring comprehensive technical test coverage across all sequential project deliverables.
- Establish and validate data quality benchmarks, including field completeness, cross-system correlation accuracy, and other contractually defined performance thresholds.
- Independently test and audit enterprise business rules, verifying analytical accuracy and controlling false-positive rates before deliverables are submitted for government review.
- Validate end-to-end ETL/ELT and data pipeline execution, including automated ingestion, Slowly Changing Dimension Type 2 (SCD2) versioning, reconciliation processes, and critical-error controls.
- Lead and coordinate UAT activities, including test scripts, test cases, execution plans, onboarding validation, and execution logs with government program staff and participating agencies.
- Compile, organize, version-control, and maintain comprehensive testing evidence, including datasets, logs, scripts, configurations, and validation documentation for independent review and system reruns.
- Verify platform performance against defined requirements, including dashboard load times, query response times, and overall pipeline execution durations.
- Manage the complete defect lifecycle, including identification, prioritization, documentation, regression testing, retesting, and closure of critical defects and schema issues.
- Conduct reproducibility audits of system documentation, business rule libraries, data dictionaries, and testing artifacts to ensure that independent third parties can reproduce validation results.
- Perform data profiling, source-to-target reconciliation, record-count verification, control-total testing, schema evolution validation, and transactional data quality assessments.
- Support independent verification and validation activities by ensuring all quality evidence is accurate, traceable, complete, and ready for formal government acceptance.
- Maintain rigorous testing standards and provide objective technical validation throughout project milestones and acceptance gates.
Requirements
- 8+ years of dedicated experience in software QA, data testing, data quality engineering, or technical systems validation.
- Demonstrated experience designing QA frameworks, user validation processes, or quantitative testing metrics within local, state, military, or federal government IT programs.
- Extensive experience testing enterprise ETL/ELT pipelines, raw-to-curated data layers, and source-to-target data reconciliation processes.
- Strong experience with financial or transactional data QA, including record-count validation, control-total testing, schema evolution, and multi-source data profiling.
- Advanced proficiency with SQL for data exploration, validation, reconciliation, and data-quality testing.
- Hands-on experience with API integration testing and structured software validation.
- Strong knowledge of regression testing, requirements-to-test traceability, performance testing, stress testing, and quantitative quality measurement.
- Experience developing structured test scripts and maintaining isolated, version-controlled datasets and testing environments.
- Expert-level understanding of defect management, quality metrics, reproducibility evidence, and formal validation documentation.
- Strong analytical and problem-solving abilities, with exceptional attention to detail and the ability to independently challenge data and system outputs.
- Preferred experience with automated data quality testing and pipeline validation in Azure Databricks or Azure Data Lake Storage Gen2.
- Familiarity with Python/PyTest, Great Expectations, Deequ, or comparable automated data quality and testing frameworks is strongly preferred.
- Experience validating Microsoft Power BI dashboards, semantic data models, and specialized reporting views is an advantage.
- Experience supporting Government Independent Verification and Validation (IV&V/ITV) processes or external agency financial audits is preferred.
- Working knowledge of Section 508 accessibility testing standards is a plus.
- Experience validating analytical models, machine-learning outlier detection, or hybrid rules-and-ML architectures is desirable.
- Candidates must be U.S. citizens or permanent residents currently located in the United States and must be able to successfully complete an FDLE Level II background screening, including fingerprinting, within five business days of contract award.
- Resumes should clearly document government customers, specific systems and testing contexts, quantitative performance thresholds, project scale, personal testing contributions, deployment or formal acceptance status, and measurable quality outcomes.
Benefits
- Part-time consultant opportunity averaging approximately 10–14 hours per week, with increased workload during active milestone acceptance gates and major validation periods.
- Remote work opportunity within the United States.
- Milestone- and deliverable-based fixed-price engagement structure.
- Opportunity to serve as a technical validation authority on a high-visibility government data and decision intelligence initiative.
- Direct ownership of quality assurance, data validation, UAT, performance testing, and formal acceptance evidence.
- Exposure to complex multi-agency data environments and enterprise-scale analytics infrastructure.
- Opportunity to apply advanced data quality, QA automation, and validation practices to a mission-critical public-sector technology program.
\nHow Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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