Data Systems Engineer, Battle Road

Onebrief

1d • Remote

About The Position

We're looking for a Data Systems Engineer who enjoys working across data pipelines, analytics, and infrastructure to turn complex systems into usable insight. You'll help design, build, and operate the data systems that underpin simulation outputs, analytics, and AI-enabled workflows across AtomEngine. In this role, you will be a key contributor on a team responsible for data infrastructure, systems, pipelines, reliability, dashboards, and ad-hoc analysis. You will work on the systems that ingest, transform, store, and expose large volumes of simulation data—enabling analytics, scenario comparison, AI/ML workflows, and explainability across the platform. You will collaborate closely with simulation engineers, AI engineers, and product teams to ensure that data is accurate, accessible, performant, and trustworthy, and to translate analytical and operational needs into durable platform capabilities.

Requirements

• 3 - 7 years of professional experience as a Data Engineer or Data Platform Engineer
• Strong experience building production data pipelines (batch and/or streaming)
• Proficiency in Python, SQL, and at least one data processing framework
• Experience with cloud-based data infrastructure (AWS, GCP, or Azure)
• Familiarity with data modeling, schema design, and data validation
• Experience working with engineers and analysts
• Ability to reason about data as a product, not a byproduct
• Due to federal contract requirements, U.S. Citizenship is mandatory for this position along with willingness and ability to get security clearance

Nice To Haves

• Familiarity with DIS (Distributed Interactive Simulation), and HLA (high level architecture)
• Experience working with government agencies
• Experience with high-volume observability and logging solutions

Responsibilities

• Design, build, and operate scheduled and event-driven data pipelines for simulation outputs, telemetry, logs, dashboards, and scenario metadata
• Build and operate data storage systems (structured and semi-structured) optimized for scale, versioning, and replay
• Support analytics, reporting, and ML workflows by exposing clean, well-documented datasets and APIs
• Enable scenario comparison, lineage, and traceability across time, versions, and parameter sets
• Work with engineers to define data contracts and schemas between the simulation environment and downstream systems
• Monitor and improve data reliability, performance, and availability

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 101-250 employees