1+ yrsBengaluruOn-siteDirect career pageEst. 6–12 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and operationalize scalable data pipelines and data platforms supporting AI products using technologies like Spark, Python, Scala, Azure Data Factory, and cloud environments (GCP/Azure).
- Develop and execute end-to-end data validation testing and QA processes, including UI-level verification and automation utilizing agentic AI frameworks with human-in-the-loop for continuous validation.
- Optimize data science workloads, manage cloud service costs, and conduct performance testing and profiling to ensure product functionality meets specifications.
Minimum Requirements
- Bachelor's degree in Engineering (B.E/B.TECH) mandatory.
- At least 1 year of experience in data engineering focused on building ETL pipelines and automation skills.
- Hands-on experience with QA, including UI and data automation testing using tools like Playwright, Selenium, and agentic AI frameworks.
- Proficient in Python, PySpark, SQL with working knowledge of cloud platforms GCP or Azure and data orchestration tools such as Azure Data Factory (DLT).
Ideal Candidate Profile
- Experienced in full lifecycle data engineering with integrated quality assurance responsibilities involving both backend and UI testing for AI-driven products.
- Comfortable working in hybrid cloud environments, leveraging modern data orchestration and testing toolsets to deliver high-volume, real-time data solutions.
- Skilled at collaborating with clients and internal teams to translate technical requirements into robust, automated data pipelines and QA workflows incorporating human-in-the-loop processes.