We are hiring a Data Engineer (5+ years) with expertise in building and managing production-scale data platforms in secure, air-gapped environments. The ideal candidate should have 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. This role requires end-to-end ownership of data pipelines, infrastructure deployment, and troubleshooting in isolated environments without cloud dependencies.

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 environments
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 environments
Comfortable working in Ubuntu-based environments with manual/local infrastructure management
Robust 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 management, and problem-solving skills

Benefits

Comprehensive insurance coverage that gives

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