Time since we first saw it
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 11,035 similar postings that came down. Coming down is not always a hire.
Work setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Design and maintain batch and real-time data pipelines in Python and SQL
Ingest and transform data from APIs, databases, satellite imagery, and public datasets
Build cloud-based data lakes, warehouses, and curated datasets on GCP or AWS
Develop data models and optimise storage, partitioning, indexing, and query performance
Build geospatial ETL workflows for NetCDF, Zarr, GeoTIFF/COG, and vector data
Design and maintain batch and real-time data pipelines using Python, SQL, and suitable orchestration tools.
Ingest and transform data from APIs, databases, satellite imagery, public datasets, and external sources.
Build cloud-based data lakes, warehouses, and curated datasets on GCP or AWS.
Develop data models and optimise storage, partitioning, indexing, and query performance.
Build geospatial ETL workflows for formats such as NetCDF, Zarr, GeoTIFF/COG, and vector data.
Open 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 11,035 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
Data Engineering - Design and maintain batch and real-time data pipelines using Python, SQL, and suitable orchestration tools. - Ingest and transform data from APIs, databases, satellite imagery, public datasets, and external sources.
- 5+ years of experience in data engineering, including production-grade data pipelines. - Strong proficiency in Python and SQL. - Experience with ETL/ELT, data modelling, APIs, relational databases, and data lake or warehouse architectures.
- Ingest and transform data from APIs, databases, satellite imagery, public datasets, and external sources. - Build cloud-based data lakes, warehouses, and curated datasets on GCP or AWS. - Develop data models and optimise storage, partitioning, indexing, and query performance.
- Experience with ETL/ELT, data modelling, APIs, relational databases, and data lake or warehouse architectures. - Hands-on experience with GCP or AWS data and infrastructure services. - Experience with PostgreSQL/PostGIS or similar databases.
- Build CI/CD pipelines for data pipelines, backend services, and ML workloads. - Use Docker and services such as Kubernetes, Cloud Run, or equivalent deployment platforms. - Implement monitoring, logging, IAM, secrets management, and cost optimisation.
- Experience with orchestration tools such as Airflow or Prefect and processing frameworks such as Spark or Dask. - Working knowledge of Linux, Docker, CI/CD, cloud networking, monitoring, and infrastructure operations. - Strong understanding of data quality, security, performance, and cost optimisation.
- Familiarity with vector databases, embedding pipelines, and RAG systems. - Exposure to Kubernetes and infrastructure-as-code tools such as Terraform. - Experience with government cloud, Digital Public Infrastructure, climate tech, or public-data systems.
- Hands-on experience with GCP or AWS data and infrastructure services. - Experience with PostgreSQL/PostGIS or similar databases. - Experience with orchestration tools such as Airflow or Prefect and processing frameworks such as Spark or Dask.
- Experience with PostgreSQL/PostGIS or similar databases. - Experience with orchestration tools such as Airflow or Prefect and processing frameworks such as Spark or Dask. - Working knowledge of Linux, Docker, CI/CD, cloud networking, monitoring, and infrastructure operations.
Complete your application on ceew.zohorecruit.in. The employer’s form will show what is required.
Already applied? Track this application
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.
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.
Council on Energy, Environment and
Water (CEEW), New Delhi
DevOps
Engineer - Tech and AI
Terms of reference
At CEEW, we are deliberate about what we stand
for (and what we don’t stand for!) as an employer. If the description below
resonates with you, we would love to hear from you!
· We offer strong visionary
leadership – with emphasis on research and impact at scale
· We actively promote leadership by
initiative
· We celebrate talent and ambition
· You will be surrounded by smart
people who will challenge you and help you grow
· You will learn faster than your
peers in other organisations
· Curiosity and irreverence, as well
as responsibility, come together at CEEW
· You will get above-market
remuneration
· We provide a safe space for all
· At CEEW, your life is your example
for others
Designation offered
Data Engineer
Focus area
Technology & AI
Duration:
Full- Time
Job duties and accountabilities
Data Engineering
Design and maintain batch and real-time data pipelines using Python, SQL, and suitable orchestration tools.
Ingest and transform data from APIs, databases, satellite imagery, public datasets, and external sources.
Build cloud-based data lakes, warehouses, and curated datasets on GCP or AWS.
Develop data models and optimise storage, partitioning, indexing, and query performance.
Build geospatial ETL workflows for formats such as NetCDF, Zarr, GeoTIFF/COG, and vector data.
Prepare reliable datasets for analytics, ML training, inference, RAG, and application APIs.
Implement data quality checks, lineage, documentation, monitoring, retries, and backfills.
Cloud and DevOps
Provision and manage cloud infrastructure required for data, geospatial, and AI workloads.
Build CI/CD pipelines for data pipelines, backend services, and ML workloads.
Use Docker and services such as Kubernetes, Cloud Run, or equivalent deployment platforms.
Implement monitoring, logging, IAM, secrets management, and cost optimisation.
Collaborate with AI, geospatial, platform, and product teams on deployment and scaling issues.
Educational Qualification
B.E./B.Tech in Computer Science, IT, or a related discipline, or equivalent relevant experience.
Relevant cloud or data engineering certifications are preferred.
Must Have
5+ years of experience in data engineering, including production-grade data pipelines.
Strong proficiency in Python and SQL.
Experience with ETL/ELT, data modelling, APIs, relational databases, and data lake or warehouse architectures.
Hands-on experience with GCP or AWS data and infrastructure services.
Experience with PostgreSQL/PostGIS or similar databases.
Experience with orchestration tools such as Airflow or Prefect and processing frameworks such as Spark or Dask.
Working knowledge of Linux, Docker, CI/CD, cloud networking, monitoring, and infrastructure operations.
Strong understanding of data quality, security, performance, and cost optimisation.
Preferred
Experience with geospatial data stacks and tools such as PostGIS, GeoPandas, Rasterio, Xarray, GeoServer, or TiTiler.
Experience supporting AI/ML workloads, GPU environments, model serving, or MLOps platforms.
Familiarity with vector databases, embedding pipelines, and RAG systems.
Exposure to Kubernetes and infrastructure-as-code tools such as Terraform.
Experience with government cloud, Digital Public Infrastructure, climate tech, or public-data systems.
Compensation
Competitive compensation – commensurate with
the experience and matching the best of the standards adopted by the industry
or other similar organisations for similar roles.
Application Process
CEEW is an equal-opportunity employer, and the
selection process does not discriminate on the basis of age, gender, caste,
ethnicity, religion, or sexuality. Female candidates are encouraged to apply.
Applications will be reviewed on a rolling
basis. Interested applicants are advised to apply at the earliest possible
time.
Only shortlisted candidates will be notified by
us. We appreciate your interest.
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NA, India
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