We're hiring a Data Engineer (5+ years) to independently design, deploy, and operate production-scale data platforms in fully air-gapped, secure customer environments - no cloud dependency, with manual deployment and troubleshooting expected. The ideal candidate has hands-on experience with Apache Airflow, Spark, PostgreSQL, Docker, Python, SQL, and S3-compatible storage (MinIO), along with strong knowledge of geospatial and time-series data, and is comfortable owning infrastructure end-to-end without managed cloud services - from data pipelines to deployment to troubleshooting in fully isolated environments.

Requirements

5+ years of experience in Data Engineering and production-scale data platforms
Design and manage Apache Airflow pipelines for high-volume sensor, satellite, and third-party data ingestion within isolated environment
Build and optimize Apache Spark workloads for batch processing, geospatial analytics, and large-scale aggregations
Develop and maintain PostgreSQL, TimescaleDB, PostGIS, and DuckDB-based data solutions
Implement efficient data ingestion, transformation,



and bulk-loading pipelines without external connectivity
Containerize and deploy applications using Docker and Docker Compose in air-gapped environments
Work with S3-compatible object storage (e.g., MinIO) for on-prem data storage
Proven experience deploying via Docker/Docker Compose in air-gapped or restricted-network environment
Comfortable working in Ubuntu-based environments with manual/local infrastructure management
Solid proficiency in Python, SQL, Airflow, Spark, and PostgreSQL
Experience with geospatial and time-series data
Collaborate with customer teams to translate business requirements into data products
Ensure data quality, lineage, observability, performance, and SLA compliance
Troubleshoot production issues on-site/remotely without cloud tooling support
Create and maintain technical documentation, data models, and operational run-books
Strong communication, stakeholder

📌 Data Engineer (New Delhi)
🏢 spark eighteen
📍 New Delhi