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Job Title: Data Engineer - Platform Engineering
Company Overview: Atreides helps organizations transform large and complex multi-modal datasets into information-rich geo-spatial data subscriptions that can be used across a wide spectrum of use cases. Currently, Atreides focuses on providing high-fidelity data solutions to enable customers to derive insights quickly.
Atreides transforms the chaos of petabyte-scale, all-domain data—land, air, sea, space, and cyber—into real-time operational clarity. We are a fast-moving, high-performance international scale company. We trust our team with autonomy, believing it leads to better results and job satisfaction. With a mission-driven mindset and entrepreneurial spirit, we are building something new and helping unlock the power of massive-scale data to make the world safer, stronger, and more prosperous.
Team Overview: We are a passionate team of technologists, data scientists, and analysts with backgrounds in operational intelligence, law enforcement, large multinationals, and cybersecurity operations. We obsess about designing products that will change the way global companies, governments and nonprofits protect themselves from external threats and global adversaries.
Position Overview: As a Data Engineer on the Platform Engineering team, you will be responsible for developing data infrastructure that powers Atreides’ core analytics systems. This includes building and optimizing high-throughput data pipelines, implementing geospatial data integration workflows, and deploying scalable services in cloud-native environments. You’ll work across systems that support complex analytics, pattern detection, and visualization over large-scale datasets. This role demands a strong understanding of distributed data systems, a hands-on approach to engineering challenges, and a commitment to building robust and maintainable infrastructure.
Team Principles:
At Atreides, we believe that teams work best when they:
- Remain curious and passionate in all aspects of our work
- Promote clear, direct, and transparent communication
- Embrace the 'measure twice, cut once' philosophy
- Value and encourage diverse ideas and technologies
- Lead with empathy in all interactions
Responsibilities:
- Design and build cloud-based data pipelines for ingesting, transforming, and storing large volumes of data.
- Implement scalable, fault-tolerant systems using modern frameworks such as Spark, Temporal, Airflow or Dagster.
- Develop APIs and services that expose reliable data access, transformation, and orchestration capabilities.
- Contribute to geospatial data processing workflows using tools such as Apache Sedona and native Iceberg geospatial functionality.
- Assist in developing and maintaining shared platform tooling and libraries that improve productivity and promote self-service capabilities across engineering and analytics teams.
- Monitor, tune, and troubleshoot the performance, cost, and reliability of data infrastructure components.
- Collaborate closely with cross-functional teams to ensure platform systems integrate smoothly with analytics, visualization, and downstream applications.
Desired Qualifications:
- 3-5 years of experience in data engineering, ideally working with large-scale or geospatial systems.
- Proficiency in Python and SQL (Spark SQL preferred); experience with distributed data processing frameworks such as Spark, Flink, or Beam.
- Familiarity with orchestration frameworks (e.g., Airflow, Temporal, Dagster) and workflow automation principles.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Exposure to batch and streaming architectures and understanding of modern data lake or lakehouse patterns (e.g., Iceberg, Delta, Hudi).
- Knowledge of geospatial data formats, processing libraries, and coordinate systems is a plus.
- Strong problem-solving skills and an interest in building reliable, scalable, and observable data systems.
Compensation and Benefits:
- Competitive salary
- Comprehensive health, dental, and vision insurance plans
- Flexible remote work environment
- Additional benefits like flexible hours, work travel opportunities, competitive vacation time and parental leave
While meeting all of these criteria would be ideal, we understand that some candidates may meet most, but not all. If you're passionate, curious and ready to "work smart and get things done," we'd love to hear from you.
