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 Software Engineer to design, build, and deploy world-class algorithms for scalable cloud processing. This individual will play a key role in delivering cutting-edge capabilities that extract actionable insights from complex data sources.

Reporting to the Director of Data Science, the Software Engineer will be responsible for leveraging their RF domain knowledge, data science and engineering skills to develop and maintain new capabilities and products at Hawkeye 360. They will receive direction from the Director of Data Science and a principal team member, with a focus on improving algorithms, systems, and capabilities that provide Hawkeye 360 customers with crucial intelligence and insights used by the US government and international allies.

The right candidate must be an innovative problem-solver with a strong background in scalable software systems, cloud-native architectures, and data-driven algorithm development. They will have experience working with large-scale data pipelines, parallel processing frameworks, and modern DevOps practices. They will also have the ability to independently take a data-intensive application from initial prototype to full-scale production deployment, demonstrating ownership across the entire development lifecycle.

The candidate will operate in a collaborative, cross-functional environment—interacting with teams across data engineering, platform engineering, and signal processing. This role will consist of designing, implementing, and optimizing core backend capabilities, supporting production deployments, and contributing to the evolution of data science and software engineering standards across the organization.

Location: This position is hybrid or remote.

As the Software Engineer - Data Science team, your main responsibilities will be:

• Write efficient, clean, and testable Python code for data science workflows
• Develop and optimize parallel processing frameworks to improve data throughput and performance
• Implement and maintain workflow orchestration using tools such as Airflow, Argo Workflows, or similar
• Design and manage cloud-native and on-prem solutions using AWS services such as S3, RDS, EC2, etc.
• Containerize applications and manage deployments using Kubernetes
• Collaborate with the Data Engineering team to integrate, optimize, and productionize advanced algorithms
• Troubleshoot and support data-intensive and machine learning applications in production environments
• Engage in collaborative software development, including code reviews, design discussions, and merge request feedback
• Work independently within a geographically distributed team

Your skills and qualifications:
Essential education and experience:

• B.S. degree in Computer Science, Electrical/Computer Engineering, or equivalent practical experience
• 3+ years of professional software development experience using Python, including proficiency with common tools and frameworks (e.g., NumPy, Pandas, SciPy, scikit-learn)
• Demonstrated experience in building and maintaining scalable data processing pipelines
• Proficient and self-sufficient in working within AWS environments, leveraging core services such as Amazon S3, EC2, etc., to build cloud-native solutions
• Hands-on experience with modern data orchestration tools (e.g., Apache Airflow, Argo Workflows)
• Strong understanding of parallel processing and performance optimization techniques
• Experience developing and maintaining DevOps best practices, including GitLab-based CI/CD pipelines
• Proficient with containerization and orchestration using Docker and Kubernetes
• Familiarity with monitoring and observability tools (e.g., Grafana, OpenTelemetry) for production systems

Desirable:​​​​​​

• Experience with Infrastructure as Code (IaC) tools such as Terraform
• Experience developing in modern C++
• Familiarity with streaming data platforms (e.g., Apache Kafka, Apache Spark)
• Experience using distributed computing frameworks (e.g., Ray, Dask, Spark) for compute-intensive tasks
• Background working with RF, acoustic, medical sensing, or other time-series data
• Knowledge of signal processing, machine learning, and numerical computing concepts

Base Salary Range: $110,000 - $150,000 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.