About Us
With more than 2 million nautical miles sailed and 50,000 days at sea, Saildrone has earned the trust of governments worldwide. Our unmanned surface vehicles (USVs) deliver continuous, real-time intelligence in the toughest oceans on Earth—giving our partners faster awareness, stronger security, and a decisive edge at sea.
Our USVs are long-range, extreme-endurance platforms powered by advanced sensors and proprietary AI - they have been designed to operate where no crewed vessel can. They collect critical insights above and below the surface to support border security, law enforcement, naval operations, and undersea infrastructure protection.
Headquartered in Alameda, CA, with offices in Washington, DC, and global deployment hubs, Saildrone operates missions worldwide. Join a fast-moving, mission-driven team at the intersection of AI, autonomy, and defense technology—where data turns into intelligence, and intelligence drives action.
The Role
We are seeking a data engineering technical leader to guide our data engineering team through execution of projects, which include building datasets of vessels at sea to catch drug smuggling, ocean floor data to map previously undiscovered underwater features, and 20Hz wind data from the middle of a hurricane. This data is transmitted over satellite in real-time, ingested into services and datastores that this team maintains, and served up to external customers, as well as our internal mission control team of maritime experts.
We expect particular focus in our vessel tracking dataset, so experience with geo-temporal data is helpful. Additionally, there is cross-functional collaboration with our machine learning team to train ML models and derive key insights from our giant dataset.
This role requires hands-on design & development as an IC (50%), staying close to the codebase, and leading cross-functional projects. Additionally, you will provide people leadership over a team of 4 ICs to help the team grow and thrive in their careers.
This role is required to be onsite in Alameda, CA in the Bay Area 3 days per week - this is our hybrid model. This is not a remote position.
Responsibilities
Work with your team, engineering leaders, and other technical/non-technical stakeholders to develop a highly reliable, low latency data pipeline, while ensuring dataset quality.
Utilize your engineering management skills to execute along a roadmap defined by business objectives, clarifying requirements, and informed by rigorous engineering design.
Work with our technical program management team to align work to schedules and ensure delivery.
Communicate in a friendly, supportive manner with engineers or other stakeholders, ensuring alignment and advocating for effective solutions.
Engage with cross-functional teams of product managers, technical program managers, technical leads, software engineers and infrastructure engineers.
Mentor and facilitate career development for individual contributors.
Drive and support a culture of rigorous design and test around software features.
Required Skills and Experience
8+ years of relevant data engineering software development
1+ years people management experience, including technical team leadership, scheduling, and resource planning
Expertise in relational databases (Postgres, AWS Aurora, PostGIS)
Working knowledge of data warehousing solutions (Athena/Presto, BigQuery, Redshift, Snowflake, or Vertica)
Familiar with Argo, Dagster, Airflow, or Luigi workflow orchestration engines
Able to provide clear priorities, and be hands on as needed to ensure successful delivery
Knowledge of software processes to produce sustainable and maintainable code
Good verbal and written communication skills
Desired Skills and Experience
Experience working with time series, geospatial, geo-temporal, or map-tile data would be a huge bonus
Experience with data from drones or robots, such as those from ROS-based systems, would also be very helpful
Expertise in Python or NodeJS programming languages
Familiar with Parquet or Protobuf data file formats
Experience with streaming technologies such Kafka, AWS Kinesis, Flink
Experience with serverless functions, such as AWS Lambda
NoSQL experience - DynamoDB, Redis, Influx, Timescale
Knowledge of visualization tools such as Jupyter Notebooks, Tableau, Streamlit
Experience with developing and deploying distributed services with Docker
Built data pipelines for Machine Learning applications
Location: This position is in Alameda, CA. Our waterfront office offers beautiful views of San Francisco Bay in always-sunny Alameda.
All employees are required to provide proof of authorization to work in the U.S. within their first 3 days of work. Please note that the Company does not sponsor employees for work visas or permanent resident cards to work in the U.S. If you need sponsorship for a work visa or green card, you will not be qualified for employment with Saildrone.
Benefits:
- Paid time off, including vacation, bereavement, jury duty, sick time and parental leave
- Comprehensive and competitive medical, dental and vision plans, and HSA with employer matching.
- Company sponsored life insurance
- Stock Options
- Annual stipend for continued learning and development
- Quarterly company BBQs at our Alameda HQ (bring your friends and family!)
- Free Bay Area Public Transportation via AlamedaTMA with the BayPass Clipper Card
Individual compensation packages are based on geographic location, scope of the role, and relevant experience, among other factors.
#LI-hybrid
Top Skills
What We Do
Saildrone provides comprehensive turnkey data solutions for maritime security, ocean mapping, and ocean data. The company provides real-time access to critical data from any ocean on earth, 24/7/365, and uses proprietary software applications to transform that data into actionable insights and intelligence. Saildrone’s fleet of uncrewed surface vehicles (USVs), powered by renewable wind and solar power, have a minimal carbon footprint and are designed to make ocean intelligence cost-effective at scale. Saildrones operate 24/7/365, without the need for a crewed support vehicle, and have sailed over 750,000 nautical miles from the Arctic to the Antarctic and spent more than 17,000 days at sea in the harshest ocean conditions on the planet.
