1

Automotive Data Engineer Jobs in Virginia (NOW HIRING)

The Software Engineer Lead will drive major corporate platform initiatives focused on enhancing ... Mobility Global provides automotive data, analytics, and software solutions across the vehicle ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

The role partners with Product, Data Engineering, Software Engineering, Analytics, and business ... Automotive or SaaS industry experience * Real-time inference and streaming platforms Success ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

The role partners with Product, Data Engineering, Software Engineering, Analytics, and business ... Automotive or SaaS industry experience * Real-time inference and streaming platforms Success ...

Merchandise Data Analyst

Staunton, VA · On-site

$50K - $65K/yr

Automotive aftermarket experience is a plus. * Three to five years of experience in Business ... Engineering or programming business applications. * Intermediate to Advanced Excel Skills.

Data Architect

Herndon, VA · On-site

$65.50 - $84.25/hr

We're ALTEN Technology USA, an engineering company helping clients bring groundbreaking ideas to ... automotive, commercial vehicles, EVs, rail, and more. As part of the global ALTEN Group--57,000 ...

Data Architect

Herndon, VA · On-site

$65.50 - $84.25/hr

We're ALTEN Technology USA, an engineering company helping clients bring groundbreaking ideas to ... automotive, commercial vehicles, EVs, rail, and more. As part of the global ALTEN Group-57,000 ...

Process Engineer

Toano, VA · On-site

$80K - $90K/yr

Greystone, a leading Tier II manufacturer in the automotive, medical, defense, and aerospace ... Measure process performance using KPIs and develop data collection systems to enhance performance.

Process Engineer

Toano, VA · On-site

$80K - $90K/yr

Greystone, a leading Tier II manufacturer in the automotive, medical, defense, and aerospace ... Measure process performance using KPIs and develop data collection systems to enhance performance.

next page

Showing results 1-20

Automotive Data Engineer information

What are some common challenges automotive data engineers face when working with vehicle data?

Automotive Data Engineers often encounter challenges related to the sheer volume and complexity of data generated by modern vehicles, including sensor, telematics, and diagnostic information. Integrating data from various sources and ensuring its quality, consistency, and security can be demanding. Additionally, collaborating with cross-functional teams—such as software developers, data scientists, and automotive engineers—requires strong communication skills to align technical requirements and project goals. Adapting to evolving automotive technologies and compliance standards is also crucial for success in this role.

What key skills and qualifications are needed to thrive as an automotive data engineer?

To thrive as an Automotive Data Engineer, you need expertise in data analytics, programming (often Python or SQL), and a strong understanding of automotive systems, typically supported by a degree in computer science, engineering, or a related field. Familiarity with big data platforms (like Hadoop or Spark), automotive communication protocols (such as CAN or LIN), and certifications in data engineering or cloud technologies are highly valued. Strong problem-solving abilities, teamwork, and effective communication help distinguish top performers in this role. These skills are crucial for developing reliable data-driven solutions that enhance vehicle performance, safety, and innovation in a rapidly evolving automotive industry.

What is the difference between Automotive Data Engineer vs Data Scientist in the automotive industry?

AspectAutomotive Data EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Data Engineering, or related field; experience with SQL, Python, big data toolsBachelor's or Master's in Data Science, Statistics, or related; proficiency in Python, R, machine learning
Work EnvironmentAutomotive companies, tech firms, data infrastructure teamsResearch labs, automotive R&D, analytics teams
Employer & Industry UsageFocus on building data pipelines, managing data infrastructure in automotive settingsFocus on analyzing data, creating models for vehicle performance, customer insights

Automotive Data Engineers primarily develop and maintain data infrastructure within the automotive industry, ensuring data flows efficiently. Data Scientists analyze this data to generate insights and predictive models. Both roles often collaborate but focus on different aspects of data management and analysis.

What is an automotive data engineer?

An Automotive Data Engineer is a professional who designs, develops, and manages systems for collecting, processing, and analyzing data generated by vehicles and automotive systems. They work with large datasets from sources such as sensors, telematics, and onboard diagnostics to improve vehicle performance, safety, and efficiency. Their role often involves collaborating with software developers, data scientists, and automotive engineers to build data-driven solutions for connected and autonomous vehicles.
What cities in Virginia are hiring for Automotive Data Engineer jobs? Cities in Virginia with the most Automotive Data Engineer job openings:
Infographic showing various Automotive Data Engineer job openings in Virginia as of August 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 100% In-person job distribution.

Software Engineer Lead

Mobility Global

Centreville, VA • On-site

Full-time

Re-posted 8 days ago


Job description

Job Summary:
S&P Global Mobility is in the process of separating its Mobility Segment into a standalone public company. The Software Engineer Lead will drive major corporate platform initiatives focused on enhancing core enterprise systems and managing platform migrations to improve reliability, security, and cost-efficiency.
Responsibilities:
• Lead the technical strategy and execution for platform enhancement, migration, and consolidation programs (e.g., application rationalization, shared services adoption, legacy retirement).
• Own end-to-end delivery: requirements discovery, solution design, implementation, testing, cutover, and post-migration stabilization.
• Set engineering direction through reference architectures, patterns, standards, and guardrails (performance, resiliency, observability, security).
• Drive technical decision-making with a bias for measurable outcomes (availability, latency, cost, deployment frequency, incident reduction).
• Design solutions to reduce duplication across corporate systems, including consolidation of services, data stores, CI/CD pipelines, and operational tooling.
• Guide modernization efforts such as service decomposition, API standardization, event-driven patterns, and cloud/platform adoption where appropriate.
• Lead integration strategies across identity, access, data, and enterprise applications.
• Define migration approaches (rehost, replatform, refactor) and execute with minimal downtime and risk.
• Create and run cutover plans, including rollback strategies, runbooks, verification checklists, and stakeholder communications.
• Manage data migration planning: mapping, transformation, validation, reconciliation, and retention/compliance considerations.
• Lead a team of engineers (directly or matrixed): provide technical guidance, unblock delivery, and uphold high engineering standards.
• Own code quality practices: design reviews, code reviews, test strategy, and technical documentation.
• Mentor engineers; build a culture of accountability, continuous improvement, and operational ownership.
• Ensure production readiness.
• Partner with security and compliance to implement secure-by-design practices (threat modeling, least privilege, auditability, secrets handling).
• Drive post-launch improvements using operational insights: incident learnings, performance bottlenecks, and customer feedback.
• Partner with Corporate platform teams, product, enterprise architecture, infrastructure, IT, and business stakeholders to align roadmap, scope, and sequencing.
• Translate business goals into technical plans; proactively manage risks, dependencies, and delivery tradeoffs.
• Communicate progress through concise status updates, technical demos, and executive-ready summaries.
Qualifications:
Required:
• Strong proficiency in one or more modern programming languages (e.g., Java, C#, Python, Go, TypeScript).
• Deep experience building distributed systems: APIs, services, asynchronous processing, caching, and data persistence.
• Experience configuring and customizing SAAS applications.
• Strong SDLC discipline: version control, branching strategies, testing pyramids, and release management.
• Proven success leading large-scale migrations (apps and/or data), including phased rollouts and zero/low-downtime strategies.
• Hands-on experience with legacy modernization and platform consolidation (decommissioning, dependency mapping, migration waves).
• Strong technical writing: architecture docs, ADRs, runbooks, operational readiness checklists.
• Ability to influence without authority and drive alignment across multiple teams.
• Pragmatic decision-making under constraints (timeline, risk, cost, regulatory needs).
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 7+ years of professional software engineering experience, including 2+ years in a lead role (tech lead, staff/lead engineer, or engineering manager with hands-on delivery).
• Demonstrated delivery of enterprise-grade platform initiatives involving migration and/or consolidation with measurable outcomes.
Preferred:
• Experience leading multi-team programs with complex dependencies.
• Experience with enterprise identity and access patterns (SSO, RBAC), data governance, and audit requirements.
• Familiarity with domain-driven design, event-driven architectures, and platform engineering practices.
• Experience with cost optimization and FinOps-style practices in cloud environments.
Company:
Mobility Global provides automotive data, analytics, and software solutions across the vehicle lifecycle. Founded in 2026, the company is headquartered in Centreville, USA, with a team of 1001-5000 employees. The company is currently Late Stage.