SDE - III (Data Platform)

Digantara is a leading Space Surveillance and Intelligence company focused on ensuring orbital safety and sustainability. With expertise in space-based detection, tracking, identification, and monitoring, Digantara provides comprehensive domain awareness across all regimes, enabling end-users to gain actionable intelligence on a single platform. At the core of its infrastructure lies a sophisticated integration of hardware and software capabilities aligned with the key principles of situational awareness: perception(data collection), comprehension (data processing), and prediction(analytics). This holistic approach empowers Digantara to monitor all Resident Space Objects(RSOs) in orbit, fostering comprehensive domain awareness.

The Data Platform Engineer will build and operate the data infrastructure powering Digantara’s Space Mission Assurance Platform, enabling scalable ingestion, processing, storage, and delivery of mission-critical space data.

• 5+ years of experience building production-grade data platforms and backend systems at scale.

• Strong expertise in Python, PostgreSQL, and Apache Airflow, with a focus on reliability, performance, and maintainability.

• Proven ability to design and operate high-volume data pipelines and platform services in cloud-native environments.

• Design, build, and maintain end-to-end data pipelines spanning ingestion, transformation, validation, and enrichment workflows.

• Develop and operate Apache Airflow-based orchestration systems integrating satellite tracking, sensor, and external data sources.

• Own PostgreSQL data architecture, including schema design, migrations, indexing strategies, and query optimization.

• Build dataset delivery and access layers through backend services, APIs, and customer-facing data interfaces.

• Ensure secure, reliable, and scalable data delivery aligned with deployment constraints and service-level requirements.

• Manage containerized deployments using Docker and support CI/CD workflows across cloud environments.

• Monitor platform health, performance, and reliability through observability and dashboarding solutions.

• Troubleshoot performance bottlenecks across pipelines, databases, storage systems, and compute infrastructure.

• Maintain high engineering standards through testing, documentation, and continuous improvement of platform capabilities.

• 5+ years of experience developing and operating production-grade data platforms.

• Strong proficiency in Python for backend and data engineering applications.

• Hands-on experience with Apache Airflow for workflow orchestration and pipeline management.

• Advanced knowledge of PostgreSQL, including schema design, indexing, query optimization, partitioning, and high-availability architectures.

• Experience designing and building REST APIs for data access and system integrations.

• Familiarity with Docker and modern CI/CD practices.

• Experience working with storage systems such as NFS and object storage platforms.

• Proficiency with Git and collaborative development workflows.

• Familiarity with AWS services such as RDS, S3, ECS, EC2, and related cloud infrastructure.

• Working knowledge of Go (Golang).

• Experience with DuckDB for analytical and OLAP workloads.

• Exposure to scientific, aerospace, or physics-based data processing pipelines.

• Strong understanding of distributed systems and large-scale data processing architectures.

• High ownership mindset with the ability to operate in a fast-paced engineering environment.

• Strong analytical and problem-solving capabilities.

• Effective communication and collaboration across cross-functional teams.

• Ability to balance rapid execution with long-term maintainability and reliability.

• Commitment to writing clean, well-tested, and well-documented code.