Shift5

Data Engineer

Remote Data Engineering role with clear candidate location fit.

PostedJul 4, 2026

Eligible countries1 accepted country

Seniority signalMiddle

Work settingRemote

Accepted candidate locations

USA

Role overview

Readable role content extracted into sections for faster review.

Design & Build Pipelines: Design, build, and maintain robust, scalable batch and streaming data processing, storage, and integration pipelines.
Feature Ownership: Interpret requirements and design specifications, taking full ownership of building features from the ground up.
Write Quality Code: Write clean, well-documented, scalable, extensible, and testable code to ensure application quality and maintainability.
Cross-Functional Collaboration: Partner with data scientists and engineers to create semantic data models representing complex vehicular systems, and integrate applications cleanly across other Shift5 componentry.
Support Stakeholders: Build scalable data products for data scientists, transportation engineers, and executives to drive insights and decision-making.
Cloud Optimization: Create efficient, reliable, cost-effective, dynamically scalable, and observable solutions utilizing AWS cloud services.
Data Analysis & Quality: Analyze complex data sets to create data ontologies, verify data quality/integrity, and ensure data accuracy throughout pipelines.
Field Support: Support the design process and occasionally travel to customer sites (estimated a few times per year) to collaborate with Field Engineers on data integration and deployment.

High-Impact Delivery: You successfully deliver scalable, observable, supportable, and reliable data processing applications that empower customers to run smarter, safer fleets.
End-to-End Ownership: You confidently steer features from initial requirements gathering and design through planning and implementation in a fast-paced environment.
Collaborative Impact: You actively shape product design alongside multidisciplinary teams, contributing directly to a culture of high performance and mission readiness.
Adaptability: You efficiently multitask and smoothly accommodate changing priorities on demand to meet the dynamic needs of a scaling company.

Engineering Experience: 2+ years of software/data engineering experience with a deep understanding of software engineering practices and concepts.
Core Languages: 2+ years of experience with a major programming language (GoLang, Java, or Python).
Databases & Big Data: 2+ years of relational database experience (PostgreSQL, MySQL, Oracle, etc.) alongside 2+ years of experience with Big Data (Hadoop, Spark) and Data Modeling.
Cloud & Containers: 2+ years of experience with containerization and cloud services (Docker, Kubernetes) and cloud monitoring tools.
Data Pipelines: Expertise with batch and streaming data pipelines using technologies such as Apache Airflow or Benthos.
Modern Data Stack: Familiarity with modern data stack components including data ingestion, transformation, and orchestration.
U.S. citizenship required and ability to obtain a security clearance.
Data Architecture: Experience and understanding of data lakes/warehouses (e.g., Snowflake, Databricks, Redshift).
DevOps Practices: Proficiency with CI/CD, source control, design reviews, and integrating observable practices.
Travel Flexibility: Willingness to travel occasionally to customer and partner sites to support field integration and deployment efforts.