The mission of the Data & Analytics group is to build high-quality ground software systems that deliver data and analytics to our customers and to establish software development best practices for the company.

HE360 is currently seeking a Senior Data Engineer / DevOps Engineer to design, build, and deploy world-class algorithms for scalable cloud processing.

The role would be part of the Data Engineering team in the Data & Analytics group. Data Engineering manages the transition to production for advance machine learning and geolocation algorithms developed by both the Processing Algorithms and Data Science teams. This team also develops and manages scalable data processing platforms for exploratory data analysis and real-time analytics to support our analysts in their geospatial data exploration needs. As a Data Engineer / DevOps Engineer, you will design and maintain scalable and efficient systems that support data science applications in training, deploying, and monitoring machine learning models. You will blend DevOps best practices with distributed data engineering to enable robust data pipelines, model serving, and experimentation environments in a cloud-native system.

We work in small teams to rapidly prototype and productize new ideas based on hands-on, in-the-weeds engineering. You'll be responsible for designing and implementing distributed backend software systems. We support a broad range of software applications to accomplish our mission, especially favoring Python and C++ languages for batch processing within cloud deployments (Kubernetes + Docker).

Location: This position is hybrid with work from home flexibility.

As the Senior Data Engineer / DevOps Engineer, your main responsibilities will be:

• Design, build, and maintain scalable distributed pipelines to support data ingestion and data processing using open-source frameworks
• Leverage tools like Apache Spark, Ray or Dask for high-performance parallel data processing
• Develop and optimize parallel processing frameworks capable of handling large-scale ingestion. Design systems that scale with data growth and model complexity
• Support distributed and parallelized ML model training across cloud environment and on-premise GPU clusters
• Containerize ML applications using Docker and deploy/manage them using Kubernetes
• Develop automated pipelines for model training, evaluation, deployment, and rollback, integrating CI/CD practices and MLOps tools to streamline workflows, reduce manual intervention, and maintain robust version control
• Implement observability for ML systems using monitoring and logging tools to track model performance, data quality, and system health
• Work closely with Processing Algorithms & Data Science teams to integrate, optimize, and deploy state-of-the-art algorithms to production-ready applications
• Apply debugging and problem-solving skills to support and troubleshoot data-intensive applications in production, with the expectation of on-call responsibility as part of the role
• Participate in collaborative software development practices, particularly performing merge request reviews, providing design feedback, etc.
• Work in a fast-paced agile environment, effectively communicate and track development activities using agile tools like JIRA/Confluence.

Your skills and qualifications:
Essential education and experience:

• B.S. degree in Computer Science, Electrical/Computer Engineering, or comparable experience
• 3+ years of professional software development experience using Python, and experience with parallel and distributing computing (e.g., Apache Spark, Ray, Dask)
• Experience with standard Python tools and frameworks (e.g. NumPy, Pandas, SciPy, SciKit)
• Experience developing and supporting DevOps best-practices
• Demonstrated experience in Docker containerization and Kubernetes for deployment and scaling and Infrastructure as Code (IaC) tools (e.g., Terraform, Crossplane or similar)
• Demonstrated hands-on experience in managing the end-to-end machine learning lifecycle using tools such as MLflow, including experiment tracking, model versioning, packaging, and deployment workflows.
• Design and manage cloud-native data solutions using AWS, including S3, RDS and other AWS services.
• Hands-on experience with on-premise GPU clusters
• Evaluated and implemented best practices for monitoring deployed models using tools such as Prometheus, Grafana

Desirable:​​​​​​

• Familiarity with data streaming platforms like Apache Kafka, Amazon Kinesis
• Experience working with modern data warehouse solutions (e.g., Snowflake, BigQuery) is a plus
• Familiarity with machine learning frameworks like PyTorch or TensorFlow is a plus.
• Working knowledge of C++ is a plus, particularly for performance optimization and handling compute-intensive workloads

Base Salary Range: $130,000 - $170,000 annually

HawkEye 360 offers a compensation package that includes a competitive base salary plus annual performance bonus and benefits. We consider many factors when determining salary offers, such as candidate's work experience, education, training & skills, as well as market and business considerations. We are also open to considering candidates with experience and qualifications at a different level than required in a job posting, which may affect the compensation package offered.

Company Overview:
HawkEye 360 is delivering a revolutionary source of global knowledge based on radio frequency (RF) geospatial analytics to those working to make the world a safer place. The company operates a commercial satellite constellation that detects, geolocates, and identifies a broad range of signals & behaviors. We employ cutting edge AI techniques to equip our global customers with high-impact insights needed to make decisions with confidence. HawkEye 360 is headquartered in Herndon, Virginia.

HawkEye 360 is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, marital status, national origin, age, veteran status, disability, or any other protected class.

To all recruitment agencies: HawkEye 360 does not accept unsolicited agency resumes. Please do not forward resumes to our jobs alias, HawkEye 360 employees or any other organization location. HawkEye 360 is not responsible for any fees related to unsolicited resumes.