Data & AI Senior Engineer - 90405345 - Washington

Your success is a train ride away!

As we move America’s workforce toward the future, Amtrak connects businesses and communities across the country. We employ more than 20,000 diverse, energetic professionals in a variety of career fields throughout the United States. The safety of our passengers, our employees, the public and our operating environment is our priority, and the success of our railroad is due to our employees.

 

Are you ready to join our team?

Our values of ‘Do the Right Thing, Excel Together and Put Customers First’ are at the heart of what matters most to us, and our Core Capabilities, ‘Building Trust, Accountability, Effective Communication, Customer Focus, and Proactive Safety & Security’ are what every employee needs to know and do to be most impactful at Amtrak. By living the Amtrak values, focusing on our capabilities, and actively embracing and fostering diverse ideas, backgrounds, and perspectives, together we will honor our past and make Amtrak a company of the future.

 

JOB SUMMARY:

 

The Data & AI Senior Engineer  advances Amtrak’s mission to make trusted, high-quality, and intelligent data broadly accessible for decision-making, automation, and innovation. This role is responsible for leading the design and delivery of complex data and AI solutions that power Amtrak’s analytics, operational systems, and digital experiences.

Senior Engineers apply deep technical expertise to architect and optimize pipelines, integrations, and data services. They ensure solutions meet performance, security, and governance standards while mentoring junior engineers and influencing design decisions across teams. The Senior Data & AI Engineer acts as both a hands-on developer and a technical leader, helping to scale Amtrak’s data and AI capabilities through standardization, reusability, and continuous improvement.

 

ESSENTIAL FUNCTIONS:

• Lead the design and evolution of scalable data and AI platform capabilities across Databricks (lakehouse), SAP data environments (e.g., Datasphere/S/4), and virtualization layers (e.g., Denodo) to deliver a unified, governed, self-service ecosystem.
• Provide hands-on technical guidance in coding, API-first integrations, model lifecycle management, pipeline development, and integration patterns.
  Architect and enforce engineering standards across ingestion, transformation, feature engineering, model deployment, and governance-as-code controls embedded directly into pipelines.
• Mentor junior and mid-level engineers, fostering skill development, collaboration, and engineering excellence.
• Partner with architects, product owners, and governance leads to align solutions with Amtrak’s enterprise data strategy and roadmap.
• Design and implement reusable platform accelerators including APIs, templates, and feature engineering patterns that enable self-service analytics and AI across domains.

MINIMUM QUALIFICATIONS:

• Education: Bachelor’s degree in Computer Science, Data Engineering, or a related technical field; equivalent experience may be considered.
• Experience: 4–6 years of experience in data engineering, software development, or data architecture.

 

PREFERRED QUALIFICATIONS:

• Experience in a leadership capacity within a scaled agile environment or data platform modernization initiative.
• Familiarity with enterprise data governance, metadata management, and security standards.
• Exposure to MLOps, cloud data platforms, and automation tools that accelerate delivery.
• Experience implementing production-grade MLOps pipelines, including model versioning, CI/CD, monitoring, and governance controls embedded into data and AI workflows.
• Prior mentorship or technical leadership of multi-functional project teams.

REQUIRED KNOWLEDGE, SKILLS and ABILITIES:

• Advanced proficiency in Python and SQL with deep experience in distributed data processing (e.g., Spark) and modern lakehouse architectures (Databricks strongly preferred), including integration of SAP data platforms and virtualization technologies into enterprise-scale solutions.
• Strong understanding of data quality, observability, and performance optimization.
• Demonstrated ability to lead teams through technical challenges while remaining hands-on in design and coding.
• Experience working within agile product teams, coordinating across multiple stakeholders.
• Strong understanding of API-first and event-driven architecture patterns, including secure service-to-service communication and role-based access control (RBAC).
• Experience embedding data quality validation,