Job Description

Location: Remote, ability to work 9:00 am - 5:00 pm Eastern Standard Time

Salary: Base $130K-$180K plus 15% annual bonus

Our client builds their own LEO satellites for RF data collection and analysis. They are currently seeking a Senior Software 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 advanced 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 Senior Software Engineer, you will work closely with their scientists to optimize algorithms for low-latency, highly scalable production environments that directly support our customers.

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).

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As the Senior Software Engineer, your main responsibilities will be:

• Write efficient, clean, and testable Python code for data engineering workflows
• Design, build, and maintain scalable ETL pipelines to support data ingestion and transformation at scale.
• Develop and optimize parallel processing frameworks to improve data throughput and performance.
• Implement and maintain pipeline orchestration using tools such as Airflow or similar.
• Design and manage cloud-native data solutions using AWS, including S3, RDS and other AWS services.
• Perform database maintenance and optimization to ensure reliability, integrity, and performance across systems.
• Containerize applications using Docker, and deploy/manage them using Kubernetes.
• 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.
• Work independently within a geographically distributed team.

Your skills and qualifications:

• B.S. degree in Computer Science, Electrical/Computer Engineering, or comparable experience
• 3+ years of professional software development experience using Python, and experience with standard python tools and frameworks (e.g. NumPy, Pandas, SciPy, SciKit)
• Proven experience in building and maintaining Extract, Transform, and Load (ETL) pipeline and data workflows.
• Hands-on experience working within an AWS environment, including knowledge of AWS services and solutions (Amazon S3, Amazon EC2)
• Experience with modern data orchestration tools (e.g., Apache Airflow, Argo CD)
• Deep understanding of parallel processing and performance optimization techniques
• Experience developing and supporting DevOps best-practices (e.g., GitLab-based CI/CD)
• Experience in Docker containerization and Kubernetes for deployment and scaling.
• Experience with monitoring and logging solutions, particularly the Grafana and OpenTelemetry (OTel) tech stack for monitoring and configuring production alerts.

Desirable: ​

• Familiar with Infrastructure as Code (IaC) tools (e.g. terraform) Knowledge of streaming data tools (e.g., Apache Kafka, Spark) Experience using Ray, Spark, Dask, or other frameworks for parallelizing and distributing compute-heavy tasks Experience with standard Python tools & framework (e.g. NumPy, pandas, SciPy, scikit)

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