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 productive data ingestion, transformation, and bulk-loading pipelines.
Containerize and deploy applications using Docker and Docker Compose, including air-gapped settings.
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 (India)
🏢 spark eighteen
📍 India