Streamhub is a data analytics and activation SaaS platform encompassing audience measurement, segmentation, and targeting. Our purpose is to understand how video shapes everyday life, and our mission is to make people's everyday lives better by being the most actionable data platform for the video business. Working at Streamhub offers unparalleled access to cutting-edge challenges in the complex adtech/media industry, within an international and rewarding entrepreneurial culture. We are in an exciting growth phase, making several key hires who will form the building blocks of our teams in India and Japan!
The Role
This role is a challenging opportunity to contribute to an innovative data product as a Data Quality Automation Engineer on our core engineering team. You will be joining a highly productive engineering team and a thriving work culture built on individual growth, well-being, strong ethics, and an entrepreneurial approach.
As a Data Quality Automation Engineer, you will be responsible for the quality of customer-facing analytics platforms and the accuracy of the data. You will join the Quality Automation function as a member of a dedicated squad. Your day-to-day work would comprise identifying, scoping, and resolving data quality problems, and determining the measures to enhance quality. Set quality standards, build test cases, and build procedures to run or automate them along with the 'Data Quality' team across Squads. Specifically, we are looking for someone who believes in automation
Responsibilities & Required Skills
- Design and maintain automated validation frameworks for ETL pipelines and large-scale data systems.
- Validate complex data transformations, aggregations, and business rules across high-volume datasets.
- Automate all the workflows related to data quality, end-to-end testing, and agent eval
- Implement robust data quality automation checks to ensure accuracy, consistency, and reliability.
- Leverage Generative AI (GenAI) to:
- Accelerate test case and script generation.
- Improve automation coverage and edge-case detection.
- Detect anomalies, regressions, and data drift.
- Enhance root cause analysis and the measurement of automation impact.
- Integrate automated validation and quality gates into CI/CD pipelines to enforce regression, schema, and contract checks before deployment.
- Build dashboards and analytics to track data quality KPIs, automation coverage, defect trends, and CI/CD effectiveness.
- Develop and maintain API and web automation frameworks (Cypress, Playwright, Selenium, or similar).
- Perform advanced SQL and database validation testing, including reconciliation and data integrity checks.
- Process and validate large volumes of structured and semi-structured data.
- Contribute to internal tools that strengthen data quality automation and intelligent validation workflows.
- Maintain strong DevOps practices using Git and CI/CD systems.
- Collaborate closely with product and engineering teams to write spec-oriented requirements and translate requirements into scalable automation solutions.
- Strong hands-on coding skills in JavaScript.
Nice to Have
- Hands-on experience with AI-assisted development tools such as Cursor or similar.
- Experience with performance testing tools such as JMeter or Gatling.
- Knowledge of additional programming languages such as Python, Java, or Scala.
- Familiarity with distributed data systems, event-driven architectures, or large-scale data platforms.
The Package
- Competitive salary.
- Immense learning, exposure to niche data technologies, and handling TBs of data.
- Work with an open, diverse, and autonomous team.
- Entrepreneurial team culture.
- Flexible timing.
If you've read all the way to the bottom of this description, thank you for your interest in Streamhub!
We are committed to equal employment opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.
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