S'INSCRIRE

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QA lead

Omni Inclusive
  • +3
  • +3
  • US
    United States
  • +3
  • +3
  • US
    United States

À propos

Key responsibilities: 1. Data Quality Strategy & Leadership: • Define and execute a comprehensive data quality testing strategy for data products, data services, and integrations. • Establish best practices for data validation, reconciliation, and anomaly detection. • Develop data quality KPIs and metrics to measure and improve data reliability. • Lead and mentor a team of data testers and QA engineers to drive excellence in data testing. 2. End-to-End Data Testing & Automation: • Oversee functional, integration, regression, and performance testing of data pipelines and ETL processes. • Implement automated data validation frameworks using Python, SQL, and cloud-native tools. • Drive the integration of test automation into CI/CD/CT pipelines for continuous data quality assurance. • Define and enforce data testing standards across teams to ensure consistency and accuracy. 3. Integration & Performance Testing : • Lead data API and service integration testing to validate data flows between systems. • Conduct performance and scalability testing to ensure the efficiency of data pipelines and queries. • Collaborate with data engineers, architects, and DevOps teams to optimize data processing workflows. 4. Governance, Compliance & Issue Resolution: • Ensure compliance with regulatory and security standards (e.g., HIPAA, GDPR etc). • Establish and maintain data lineage, metadata validation, and data governance controls. • Manage and drive resolution of data quality issues, defects, and anomalies through proactive monitoring. • ct as a liaison between Product leaders, Delivery Leaders / Technical managers, End Users and QA Testers to ensure alignment on data quality goals .
Required Work Experience: Lead and drive the end-to-end data quality strategy for our enterprise data products and services. Required: • 15+ years of experience in data quality testing, data validation, or data engineering QA, with at least 3+ years in a leadership role. • Expertise in data warehouse, data lake, and ETL testing on cloud-based platforms (preferably GCP BigQuery). • Strong proficiency in SQL and Python for data validation and automation. • Experience with data testing frameworks (e.g., Great Expectations, dbt tests, Deequ). • Proven track record of test automation, CI/CD integration, and performance testing. • Defining Test Data requirements / Test Bed for large projects / programs • Strong analytical and problem-solving skills with the ability to debug complex data issues. • Excellent leadership, communication, and stakeholder management skills. Preferred: • Experience in healthcare data platforms and compliance regulations (HIPAA, FHIR, HL7). • Familiarity with data observability, metadata management, and governance tools (e.g., Collibra, Monte Carlo). • Knowledge of GCP data services, including Dataflow, Pub/Sub, and Cloud Storage. • Experience in data API testing and service validation.

Compétences idéales

  • Python
  • SQL
  • Test Automation
  • United States

Expérience professionnelle

  • Data Engineer
  • QA Test Automation
  • QA Manual Test

Compétences linguistiques

  • English
Avis aux utilisateurs

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