Data Analysis and Engineer

About Vatn Systems: Vatn Systems is an innovative startup at the forefront of designing and manufacturing autonomous underwater vehicles (AUVs). Our mission is to revolutionize underwater security, exploration, research, and operations through cutting-edge technology and unparalleled engineering. Our AUVs are defining the next generation of underwater autonomy. The Role We are looking for a talented and motivated Data Engineer / Analyst to join our growing team. Every vehicle we put in the water generates gigabytes of navigation, sonar, acoustic, and vehicle-health data, and today that data is underused. In this role, you will own the pipeline that turns raw mission logs into answers. The ideal candidate is a proactive individual who is comfortable owning data infrastructure end to end and who is as interested in the physics and purpose behind the data as in the plumbing that moves it. What You'll Do Design, build, and maintain data pipelines that ingest post-mission logs from vehicles and field kits into a queryable, durable data store. Develop reusable statistical analysis tooling in Python and/or Matlab for post-mission reconstruction, including coordinate frame handling, time alignment across asynchronous sensors, and navigation error characterization. Build and maintain dashboards and reports that communicate vehicle and subsystem performance clearly to engineers, leadership, and customers. Define and track quantitative performance metrics across programs and make trends visible over time. Establish data schemas, naming conventions, and metadata standards so that test data is discoverable and traceable to a specific vehicle, build, and configuration. Support field test campaigns by turning around rapid analysis between runs and flagging anomalies before the next deployment. Build automated data quality checks and monitoring to catch dropped telemetry, clock issues, and sensor faults early. Produce analysis products that feed customer deliverables, test reports, and internal design reviews. Write and maintain documentation and tests so that pipelines and analyses are reproducible by others on the team. What You'll Need Required Qualifications: Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Physics, or a related technical field (or equivalent practical experience). Professional experience in data engineering, statistical analysis, or a comparable role. Strong proficiency in Python, Matlab and/or R data ecosystems (e.g., NumPy, pandas, Polars). Strong SQL skills and experience designing schemas for relational or time-series databases. Experience building and maintaining ETL/ELT pipelines that handle large, messy, real-world sensor or log data. Familiarity with statistical methods, data transformation techniques, and data visualization. Experience building dashboards or visualization tooling (e.g., Grafana, Plotly/Dash, Streamlit). Ability to work…