Data Engineer

Why LeoLabs? At LeoLabs, we’re building the living map of activity in space. Through our proprietary global radar network and AI-enabled analytics platform, we collect millions of measurements daily on more than 25,000 objects in low Earth orbit (LEO). Our radar-powered intelligence protects billions in assets, monitors adversarial behavior, and ensures safe operations for commercial and government missions. We’re not just building technology, we are redefining global security, safety, and transparency in space. As orbital activity accelerates and threats grow more complex, LeoLabs is a trusted partner for Space Domain Awareness, Space Traffic Management, and Satellite Operations for top-tier space operators and allied defense organizations. If you're looking to work on mission-critical challenges at the forefront of aerospace, national security, and AI, your impact starts here.   The Opportunity  We are seeking a motivated and hands-on early career Data Engineer to join LeoLabs’ growing Insights team. You will play a key role in building and operating the data pipelines and analytics infrastructure that power customer insights, internal decision-making, and real-time space domain awareness capabilities.    You will work closely with software engineers, radar and catalog teams, and data scientists to ensure reliable extraction, transformation, and loading (ETL) of mission-critical datasets. This includes developing scalable batch and streaming data workflows, enabling advanced analytics, and supporting machine learning initiatives.    Your contributions will help transform large volumes of sensor and orbital data into actionable intelligence that enables users to safely operate and manage assets in low-Earth orbit. This early career role is primarily hands-on development, with opportunities to grow into increased ownership of data platform design and optimization.  Qualifications  Must be eligible to obtain and maintain a U.S. personnel security clearance B.S. or M.S. in Computer Science, Data Science, Engineering, Mathematics, Physics, or equivalent experience  0-2 years of experience in data engineering, software engineering, analytics engineering, or related technical roles Experience designing and building data pipelines or ETL/ELT workflows  Hands-on experience with Databricks, Apache Spark, or distributed data processing frameworks  Proficiency in Python and SQL for data transformation and analysis  Familiarity with data modeling concepts and modern data lake or warehouse architectures  Experience working in cloud-native environments (AWS preferred)  Understanding of software development best practices including version control, testing, and CI/CD  Strong analytical mindset and ability to troubleshoot complex data issues  Effective communication skills and ability to collaborate across distributed engineering teams  Ability to participate in operational support rotations during critical incidents    Data Preferred Qualifications  Experience supporting data science or machine learning workflows, including feature engineering pipelines  Familiarity with Delta Lake, Lakehouse architectures, or large-scale telemetry data processing  Exposure to streaming data systems such as Kafka or Spark Structured Streaming  Experience with workflow orchestration tools such as Airflow or Databricks Workflows  Background in orbital mechanics, aerospace, physics, or applied mathematics  Experience building analytics datasets or semantic models for BI tools  Active U.S. security clearance or ability to obtain one    Within 1 Month, You’ll  Complete onboarding to gain familiarity with LeoLabs’ mission, products, and data platform  Successfully configure development environments, tooling, and data access  Participate in team ceremonies and begin ramping up on existing data pipelines and platform services  Deliver initial low-risk improvements such as pipeline enhancements, monitoring updates, or documentation contributions    Within 3 Months, You’ll  Develop working knowledge of LeoLabs’ data architecture, ingestion systems, and Databricks workflows  Contribute to building and maintaining small-to-medium data pipeline features  Collaborate with data scientists and product stakeholders to support analytics and modeling initiatives  Improve pipeline reliability, performance, and observability    Within 6 Months, You’ll  Demonstrate solid understanding of platform architecture and operational practices  Independently deliver well-tested and scalable data workflows  Take ownership of defined datasets or pipeline components    Within 12 Months, You’ll  Demonstrate proficiency across LeoLabs’ data engineering stack and cloud data platform  Deliver pipeline enhancements end-to-end with minimal oversight  Contribute to architecture discussions and platform roadmap planning  Identify opportunities to improve data quality, scalability, and mission impact    Perks and Benefits Global workforce: flexible remote/hybrid opportunities Work on complex, meaningful missions with real-world impact Unlimited paid time off for most roles Competitive salary and equity packages Comprehensive health, dental, and vision coverage Access to the forefront of commercial space operations and defense innovation   All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identify, national origin, disability, or status as a protected veteran.