Skip to main content

Rhombus Power, Inc.

Data Engineer, Palo Alto

Palo Alto, California, United States$110k–$180kmidAdded today

About this role

Rhombus Power seeks a Data Engineer to design and maintain data infrastructure and pipelines supporting AI-powered defense and national security applications. You'll develop code for data ingestion, build scalable platforms, and collaborate across teams to deliver mission-critical analytics solutions.

What you'll do

  • Develop automation scripts in Python and other languages to improve data ingestion and management processes
  • Architect data repositories, platforms, and ETL pipelines for ingestion, transformation, and aggregation
  • Extract and analyze raw data from multiple sources via APIs, SQL, and Python scripts
  • Review and optimize data architecture, governance, quality, and metadata management
  • Build and maintain scalable data platforms while monitoring performance and supporting operations
  • Communicate project status and results to leadership across the organization

What they're looking for

  • Python, Pandas, and NumPy
  • SQL and relational databases (MySQL, PostgreSQL, Oracle, SQL Server)
  • NoSQL databases (MongoDB, DynamoDB, HBase)
  • ETL pipeline design and development
  • AWS or cloud platform technologies
  • Query optimization and data modeling
  • APIs and data extraction techniques
  • Machine learning frameworks (TensorFlow, Scikit-Learn)
Apply with Autofill

Opens the application — the Jobs AI extension fills it for you. Set up autofill

Opens the official application on the employer’s site. No login required.

Rhombus Power, Inc.

Rhombus Power, Inc. builds data infrastructure and software solutions for national security projects, requiring security clearances. The company is hiring DevOps engineers and data engineers to deploy systems, develop data pipelines, and support mission-critical infrastructure.

View all jobs at Rhombus Power, Inc.

Likely interview questions

  • Describe your experience building and maintaining ETL pipelines—what tools and technologies have you used, and what challenges did you face?
  • Walk us through how you've optimized database queries or data models in a previous role.