QA Leader - Data and Integrations

Overview

Remote
Depends on Experience
Full Time
Accepts corp to corp applications

Skills

API

Job Details

QA Leader - Data and Integrations

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.
  1. 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.
  1. 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.
  1. 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.
  • Act 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 Google Cloud Platform 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 Google Cloud Platform data services, including Dataflow, Pub/Sub, and Cloud Storage.
  • Experience in data API testing and service validation.

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