Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 6 and day 54.
At Bayer, jobs usually come down by about day 14.
From 11,508 similar postings that came down, and 55 of Bayer’s. Coming down is not always a hire.
Data Engineer
Bengaluru, KA, IN
Actively hiring, first seen by us 1 day ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingBuild, test, and maintain data pipelines and data-product components
Troubleshoot pipeline failures, data-quality anomalies, and performance bottlenecks
Optimize pipeline performance and cloud infrastructure costs
Document pipeline designs, data lineage, and operational runbooks
Coach less-experience colleagues on data-engineering patterns and tooling
From the employer’s posting
build, test, and maintain data pipelines and data-product components
Troubleshoot pipeline failures, data-quality anomalies, and performance bottlenecks
Optimize pipeline performance and cloud infrastructure costs
Document pipeline designs, data lineage, and operational runbooks
Coach less-experience colleagues on data-engineering patterns, testing practices, and cloud-platform tooling
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 6, 20261 day ago
- Recorded sightings
- 2
- Last seen by us
- Nov 7, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Bayer is hiring
22 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is picking up
- Takes jobs down at a usual pace
- 5% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Java
- Python
- R
- Scala
- SQL
- AWS
- Azure
- Databricks
- dbt
- Delta Lake
- GCP
- Iceberg
- S3
- SageMaker
- Snowflake
- Spark
- Terraform
- Airflow
- PySpark
Where the posting names them
Apply cloud and big-data engineering skills to build, test, and maintain data pipelines and data-product components using tools such as Spark, dbt, Airflow, or equivalent cloud-native services. Execute ingestion, transformation, and loading jobs that reliably move data from operational systems, IoT devices, or clinical sources into data platforms at agreed SLAs. Troubleshoot pipeline failures, data-quality anomalies, and performance bottlenecks, diagnosing root causes and implementing fixes without service disruption. Validate that implemented pipelines meet data contracts, schema standards, and access-control policies defined by data architects and governance teams. Optimize pipeline performance and cloud infrastructure costs by profiling job runtimes, partitioning strategies, and resource configurations. Document pipeline designs, data lineage, and operational runbooks in shared repositories accessible to data consumers and support teams. Coach less-experience colleagues on data-engineering patterns, testing practices, and cloud-platform tooling used in the assigned domain. Reference Code:| 894554 | | --- Contact Us + 022-25311234 Required - Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field, 6+ years of experience Proficiency in SQL, Python, PySpark, Spark, or another Programming language, such as Java, Scala or R Proven experience building highly scalable, performant, resilient, and cost-optimized data pipelines Experience with modern data processing frameworks, such as Snowflake, Databricks, or AWS SageMaker Unified Studio Hands-on experience with core AWS services, including Amazon S3, IAM, Lake Formation, AWS Glue, Lambda, and related services required to build, operate, and secure end-to-end data solutions Strong understanding of relational databases and modern lakehouse table formats (Apache Iceberg, Delta Lake) Expertise in design, build, maintain and document conceptual, logical, and physical data models Sound understanding of data governance principles, access control, data cataloging, lineage, encryption, auditability, and compliance requirements. Ability to implement secure cloud environments and role-based access controls using IAM and Lake Formation. Familiarity with the concept of Retrieval-Augmented Generation (RAG) data pipelines Familiarity with data architecture patterns, such as data hub, mesh, or fabric Experience with RESTful APIs and data integration Familiarit with the Data Product concept and hands-on implications Relevant certifications (e.g., GCP Certified, AWS Certified, Azure Certified) Demonstrated experience with Terraform for infrastructure automation, together with Git, GitHub, GitHub Actions, and CI/CD practices. Experience with GxP and computerized system validation
Your next step
Complete your application on talent.bayer.com. The employer’s form will show what is required.
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Already applied? Track this application
Has Bayer posted this job before?
Yes. We’ve followed 2 other Data Engineer jobs there since May 2026. All 2 are still up.
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 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.
About the role
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.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
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.
Job description
Apply cloud and big-data engineering skills to build, test, and maintain data pipelines and data-product components using tools such as Spark, dbt, Airflow, or equivalent cloud-native services. Execute ingestion, transformation, and loading jobs that reliably move data from operational systems, IoT devices, or clinical sources into data platforms at agreed SLAs. Troubleshoot pipeline failures, data-quality anomalies, and performance bottlenecks, diagnosing root causes and implementing fixes without service disruption. Validate that implemented pipelines meet data contracts, schema standards, and access-control policies defined by data architects and governance teams. Optimize pipeline performance and cloud infrastructure costs by profiling job runtimes, partitioning strategies, and resource configurations. Document pipeline designs, data lineage, and operational runbooks in shared repositories accessible to data consumers and support teams. Coach less-experience colleagues on data-engineering patterns, testing practices, and cloud-platform tooling used in the assigned domain. Reference Code:| 894554 | | --- Contact Us + 022-25311234 Required - Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field, 6+ years of experience Proficiency in SQL, Python, PySpark, Spark, or another Programming language, such as Java, Scala or R Proven experience building highly scalable, performant, resilient, and cost-optimized data pipelines Experience with modern data processing frameworks, such as Snowflake, Databricks, or AWS SageMaker Unified Studio Hands-on experience with core AWS services, including Amazon S3, IAM, Lake Formation, AWS Glue, Lambda, and related services required to build, operate, and secure end-to-end data solutions Strong understanding of relational databases and modern lakehouse table formats (Apache Iceberg, Delta Lake) Expertise in design, build, maintain and document conceptual, logical, and physical data models Sound understanding of data governance principles, access control, data cataloging, lineage, encryption, auditability, and compliance requirements. Ability to implement secure cloud environments and role-based access controls using IAM and Lake Formation. Familiarity with the concept of Retrieval-Augmented Generation (RAG) data pipelines Familiarity with data architecture patterns, such as data hub, mesh, or fabric Experience with RESTful APIs and data integration Familiarit with the Data Product concept and hands-on implications Relevant certifications (e.g., GCP Certified, AWS Certified, Azure Certified) Demonstrated experience with Terraform for infrastructure automation, together with Git, GitHub, GitHub Actions, and CI/CD practices. Experience with GxP and computerized system validation
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bengaluru, KA, IN
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.