Geospatial Data Engineer - Onsite TS/SCI Clearance

Vantor Inc.; Herndon (VA); On-site; USD 116,000 - 169,000; Full time

Benefits offered by this job

401(k) with company match

Mental health resources

Student loan repayment assistance

Adoption reimbursement

Pet insurance

Job summary

Vantor Inc. is seeking a solution-driven Software Engineer to work onsite with U.S. Government customers, delivering data collection, analytics, visualization, and workflow automation solutions.

You will collaborate with analysts to understand mission needs, handle large geospatial datasets, and apply cloud processing and data science techniques. A fast-paced, innovative environment encourages trying new approaches and learning from failures.

Qualifications

• US citizenship and TS/SCI clearance (with CI poly) required.
• Bachelor's degree in Computer Science or related field.
• Minimum 5 years of software development experience.
• Proficiency in Java or Python or Go or Rust.
• Experience with data extraction, manipulation, visualization, and analysis of large datasets.
• Experience designing cloud-based architectures (AWS) and NoSQL data stores (Elasticsearch, MongoDB).

Responsibilities

• Design and implement scalable software for mission-critical applications.
• Active in all aspects of the development lifecycle from planning to maintenance.
• Apply software standards to produce high-quality, extensible solutions.
• Work with cloud stacks to extract, transform, visualize geospatial-temporal data.
• Develop analytics products to help users derive insights.
• Collaborate with analysts, engineers, clients, and users; work onsite full-time.

Skills

Java

Python

Go

Rust

Linux

Education

Bachelor's degree in Computer Science or related field

Tools

Elasticsearch

MongoDB

Docker

Kubernetes

AWS

Job description

Vantor Inc. is seeking a solution-driven Software Engineer to work onsite with U.S. Government customers, delivering data collection, analytics, visualization, and workflow automation solutions.

You will collaborate with analysts to understand mission needs, handle large geospatial datasets, and apply cloud processing and data science techniques. A fast-paced, innovative environment encourages trying new approaches and learning from failures.