Data Engineer
NA, India
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
Tools in this posting
- Python
- SQL
- AWS
- Docker
- Google Cloud (GCP)
- Kubernetes
- Prefect
- Spark
- Airflow
- PostgreSQL
- Terraform
- Dask
Source — Tool mentions in context
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.
- 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.
- 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.
Posting record
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- First seen by us
- Jun 3, 2026 · 135d ago
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- Last seen by us
- Oct 16, 2026
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Job description
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!
At CEEW, we build careers in public policy
· 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
Location
New Delhi, India
Duration:
Full- Time
Job duties and accountabilities
Roles &
Responsibilities
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.
Selection Criteria
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on ceew.zohorecruit.in. The employer’s form will show what is required.
Already applied? Track this application
Source details
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- Location & working pattern
NA, India
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