Bengaluru, India
Actively hiring, first seen by us 6 hours agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design and build parameterized data pipelines that feed AI products
Write data transformation code in Spark (Python and Scala) and Dask
Build data validation tests using agentic frameworks with human-in-the-loop checks
Verify product functionality from backend and UI against requirements
Document defects with clear test and reproduction steps
Develop productized and parameterized data pipelines that feed AI products leveraging GPUs and CPUs.
Develop efficient data transformation code in spark (in Python and Scala) and Dask.
Develop data validation tests to assess the quality of the data using agentic frameworks
Verifies Product functionality both from backend and UI against user requirements or specification
Documents defects with clearly described test steps and reproduction steps
Looking for B.E/ B.TECH Engineering .
Looking for candidate with hands on QA -UI and Data automation with agentic AI experience
Experience in data engineering for building ETL pipelines
Candidates must possess a deep understanding of databases, SQL, cloud technologies, and modern data integration and orchestration tools (such as Azure Data Factory)
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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• Develop productized and parameterized data pipelines that feed AI products leveraging GPUs and CPUs. • Develop efficient data transformation code in spark (in Python and Scala) and Dask. • Develop data validation tests to assess the quality of the data using agentic frameworks
Experience in data engineering for building ETL pipelines . Looking for 1+ years' experience with automation skill .. Python , PySpark GCP/ Azure , DLT ,LLM , RAG, Playwright, Selenium, SQL Benefits:
What We're Looking For: A Data and QA Engineer in this role will be responsible for understanding client technical requirements and designing and building robust data pipelines to support them. Because this is a highly fungible, end-to-end role, the candidate must span both development and quality assurance. Beyond hands on ETL development and solution building, they will be responsible for loading data, performing end-to-end testing, and verifying that the processed data is accurately represented in the software product's UI.To achieve this, the engineer will build and automate data pipelines while validating results at the UI level using Agentic AI QA and development workflows, incorporating necessary human-in-the-loop processes. Success in this role requires strong verbal and written communication skills to interface effectively with both clients and internal teams. Candidates must possess a deep understanding of databases, SQL, cloud technologies, and modern data integration and orchestration tools (such as Azure Data Factory). Additionally experience in data and UI testing across software products is required• Play a critical role in the design and implementation of data platforms for the AI products. • Develop productized and parameterized data pipelines that feed AI products leveraging GPUs and CPUs.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Overview:
At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges.
Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.
You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally.
Come make an impact every day at Zebra.
What We're Looking For:
A Data and QA Engineer in this role will be responsible for understanding client technical requirements and designing and building robust data pipelines to support them. Because this is a highly fungible, end-to-end role, the candidate must span both development and quality assurance. Beyond hands on ETL development and solution building, they will be responsible for loading data, performing end-to-end testing, and verifying that the processed data is accurately represented in the software product's UI.To achieve this, the engineer will build and automate data pipelines while validating results at the UI level using Agentic AI QA and development workflows, incorporating necessary human-in-the-loop processes.• Play a critical role in the design and implementation of data platforms for the AI products.
• Develop productized and parameterized data pipelines that feed AI products leveraging GPUs and CPUs.
• Develop efficient data transformation code in spark (in Python and Scala) and Dask.
• Develop data validation tests to assess the quality of the data using agentic frameworks
incorporating necessary human-in-the-loop processes to continuously validate and ensure automation effectiveness
• Verifies Product functionality both from backend and UI against user requirements or specification
• Verifies bug reports provided by customers, works with customers to specify reproduction steps
• Documents defects with clearly described test steps and reproduction steps .
• Conduct performance testing and profiling of the code using a variety of tools and techniques.
• Build data pipeline frameworks to automate high-volume and real-time data delivery for our data hub. • Operationalize scalable data pipelines to support data science and advanced analytics.
• Optimize customer data science workloads and manage cloud services costs/utilization.
Experience
Looking for B.E/ B.TECH Engineering .
Looking for candidate with hands on QA -UI and Data automation with agentic AI experience
Experience in data engineering for building ETL pipelines .
Looking for 1+ years' experience with automation skill .. Python , PySpark GCP/ Azure , DLT ,LLM , RAG, Playwright, Selenium, SQL
Benefits:
We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success.
Job Posting Statement:
To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.
AI Technology Statement:
Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people. For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy.
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Bengaluru, India
Benefits: We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success. Job Posting Statement:
No clear work-authorization passage found. Eligibility is unconfirmed.