What You’ll Do:
We are seeking a highly skilled and self-directed Senior QA Engineer/SDET to drive comprehensive quality engineering for our Enterprise Data & Analytics Platform. Reporting into the Sr. Director – Analysis, Change and Quality, this role will own and implement advanced automated testing strategies across the entire data lifecycle, ensuring data reliability, data quality, and AI/BI model accuracy. This role requires deep technical expertise in automation tools to test data pipelines in data bricks and data quality frameworks.
Responsibilities will include but are not limited to:
· Architect and implement robust automated testing frameworks leveraging PySpark and Databricks-native tools for data validation across Raw, Curated, and Mart layers.
· Design and implement data quality validation frameworks, including checks on accuracy, completeness, and consistency across transformation layers.
· Create advanced data quality KPIs, integrating them into automated dashboards to track quality trends across layers.
· Design metadata-driven tests, integrating with CI/CD pipelines, with coverage on all transformation layers.
· Lead development of QA user stories and acceptance criteria, precisely defining test scenarios for ingestion, transformation, and consumption layers.
· Perform complex data reconciliation testing across 10+ source systems, ensuring accuracy, completeness, and consistency from source through Mart.
· Own the end-to-end testing lifecycle (QA, Staging, Production), defining what and when to test at each stage and ensuring sign-off criteria are met.
· Partner closely with data engineers to troubleshoot pipeline failures, connectivity issues, and performance bottlenecks.
· Set standards for data lineage and auditability, ensuring every transformation step can be validated and traced.
· Plan, facilitate, and manage User Acceptance Testing (UAT) involving business users for data visualization tools such as Tableau running on Databricks.
· Prepare UAT test scenarios aligned with business use cases, guide users through testing, and gather actionable feedback.
· Drive defect triage, resolution, and retesting, ensuring readiness for production release.
· Work within a SAFe Agile framework, participating in PI planning, sprint ceremonies, and cross-team coordination. Collaborate with DevOps, Data Engineers, Data Scientists, and Product Owners to integrate QA into CI/CD pipelines.
· Provide regular updates to project and senior management on progress of QA milestones and tasks.
What you'll need:
· Minimum of 5+ years of solid experience in Data Engineering with proven experience testing and validating data pipelines in Databricks, including medallion architecture.
· Proficient in creating testing framework for validating Data Quality.
· Proficient in Databricks notebook, PySpark, Python, SQL, and data quality testing.
· Expert with testing AI/BI models, ensuring data quality from feature engineering through model scoring.
· Experience in CI/CD pipelines (e.g., Azure DevOps) for automated test execution.
· Strong knowledge of data governance (data lineage, audit trails, compliance testing).
· Excellent problem-solving skills with the ability to work in a fast-paced environment.
· Experience with tools such as Azure Purview and Profisee MDM is preferred.
Equal Employer/Veterans/Disabled
Navitas Business Consulting is an affirmative action and equal opportunity employer. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Navitas Human Resources.
Navitas is an equal opportunity employer. We provide employment and opportunities for advancement, compensation, training, and growth according to individual merit, without regard to race, color, religion, sex (including pregnancy), national origin, sexual orientation, gender identity or expression, marital status, age, genetic information, disability, veteran-status veteran or military status, or any other characteristic protected under applicable Federal, state, or local law. Our goal is for each staff member to have the opportunity to grow to the limits of their abilities and to achieve personal and organizational objectives. We will support positive programs for equal treatment of all staff and full utilization of all qualified employees at all levels within Navitas.