• Design and implement complex Spark data logic, focusing on performance optimization, data volume tuning, and robust execution. • Own the architectural design of graph build pipelines, ensuring they are scalable, automated, and highly resilient. • Plan and oversee the strategic re-architecture of data pipelines to meet evolving business needs and scale. • Optimize infrastructure-as-code and schema designs to reduce cloud costs and improve pipeline latency. • Act as a technical consultant for the team, fostering a collaborative and engineer-led approach to design decisions. • Support the development of the engineering team through code reviews, design docs, and architectural best practices. • Ensure the accuracy of mission-critical data outputs.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We’re seeking a skilled Data Engineer to build the next-generation data management and artificial intelligence platform for maritime domain awareness. What you’ll do: - Implement real-time data pipelines with MQTT and Redpanda for stream processing. - Implement offline data pipelines using Dagster for batch processing. - Parse and process binary message formats from various data sources. - Build data warehouses using Postgres, Apache Iceberg, Parquet, and S3. - Design data models that allow for high-performance queries. - Validate and normalize data sources. - Improve local development and CI/CD using modern tooling and GitHub Actions. Qualifications - Expertise in time-series data processing and analysis (windowing, resampling, interpolation, etc.) - Proficiency in Python and Rust for data engineering workflows. - Experience with binary message parsing. - Experience with row-based & columnar-based data formats. - Experience with OLTP & OLAP databases. - Knowledge of distributed systems, streaming architectures, and batch processing patterns. - Hands-on experience with a batch orchestrator such as Dagster/Airflow. - Hands-on experience with a streaming platform such as Redpanda/Kafka. - Hands-on experience with binary message formats such as Protobuf. Requirements - Experience with IoT devices and sensors (nice to have). - Digital signal processing experience (nice to have). - Geospatial analysis and GIS experience (nice to have). - Familiar with working in monorepos (nice to have). Benefits - Unlimited PTO — Take the time you need to recharge and maintain work-life balance. - Dedicated Sick Time — Your health and well-being come first. - Comprehensive Health & Benefits – Medical, dental, and vision coverage to keep you and your family protected. - 11 Paid Holidays — Enjoy time off throughout the year to celebrate and spend time with loved ones. - Professional Development — Educational opportunities and resources to help you grow your skills and advance your career. - Collaborative Environment — Work directly with leadership in our flat organizational structure, where your ideas and contributions matter. - Mission-Driven Work — Contribute to projects that directly support national security and make a real-world impact. - Growth Opportunities — Join us during an exciting expansion phase where you can help shape our future. - 401(k) with company match. - Onsite / Remote / Flexible work arrangements or hybrid options (position dependent). - Relocation assistance (position dependent). - Referral bonuses. - Performance bonuses. - Life insurance and disability coverage. - Technology home office setup stipend. - Professional certification reimbursement (position dependent).

• Design and build robust data pipelines that integrate data from diverse sources to support risk evaluation and business intelligence • Build streaming data pipelines using Kafka and AWS services to enable real-time data processing and decision-making • Create and operate data services that make curated datasets accessible to internal teams and external partners through APIs and scheduled deliveries • Support data science workflows by building infrastructure that enables model training, feature engineering, and production inference • Implement data quality frameworks including validation, monitoring, and alerting to maintain trust in our data assets • Contribute to CI/CD pipelines and infrastructure-as-code practices to ensure reliable, repeatable deployments • Deliver highly reliable services by following engineering best practices and participating in an on-call rotation to support production systems • Contribute to the data warehouse by creating well-modeled datasets in Snowflake that empower analysts and data scientists • Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions that drive value

• Design, build, and maintain efficient ETL/ELT processes and reliable data pipelines in dbt and BigQuery, integrating data from a variety of sources (MongoDB, SQL, Google Sheets, Google Analytics, APIs, etc.); • Build and maintain dashboards and visualizations in Looker Studio and other BI tools; • Ensure data quality, consistency, and accessibility across the organization, implement data quality controls; • Proactively collaborate with different stakeholders across operations, sales, finance and tech to clarify requirements and answer data-related questions.