Job Description
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 workplace

- 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

- Strong 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 you peace of mind, so you can focus on doing your best work

- Flexible work arrangements designed to support sustained productivity, personal well-being, and work-life balance

- Continuous learning and accelerated skill development through hands-on projects and mentorship from experienced industry leaders

- Global client exposure across 20+ countries, offering real-world experience with diverse markets and business environments.

- Opportunity to work on high-impact, large-scale projects that have collectively generated over $1B in measurable business value

- Competitive, market-aligned compensation packages that recognize performance, expertise, and long-term contribution

- Monthly demo days that celebrate innovation, showcase your work, and give you a real voice in what we build

- Annual recognition programs and performance-driven awards in a truly meritocratic environment

- Referral bonuses that reward you for helping grow a strong, like-minded team

- A strong problem-solving culture with opportunities to tackle meaningful, real-world challenges

- A positive, people-first workplace that supports happiness, balance, and long-term growth

Requirements
Programming: Python Libraries: Pandas, SQLAlchemy, Airflow Operators Database & Query Languages: SQL (Intermediate to Advanced) Orchestration Tools: Apache Airflow, Prefect Data Warehouses: PostgreSQL, Redshift, Big Query Cloud Platforms: AWS, GCP, Azure Containerization / Environments: Docker, Virtual Environments Version Control: Git

📌 Data Engineer - Senior (India)
🏢 spark eighteen
📍 India