Role & responsibilities

- 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.

- 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.

- Containerize and deploy applications using Docker and Docker Compose, including air-gapped environments.

- Collaborate with customer teams to translate business requirements into data products and analytical solutions.

- Ensure data quality,



lineage, observability, performance, and SLA compliance.

- Troubleshoot production issues and optimize pipeline, database, and query performance.

- Create and maintain technical documentation, data models, and operational runbooks.

- Demonstrate robust proficiency in Python, SQL, Airflow, Spark, and PostgreSQL.

- Experience with geospatial and time-series data, S3-compatible storage, and secure customer environments.

- Strong communication, stakeholder management, and problem-solving skills.

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