Data & AI Engineer - 90408785 - Remote

Amtrak•Washington, DC

23d•$72,000 - $93,312•Remote

About The Position

The Data & AI Engineer Specialist plays a key role in delivering Amtrak’s enterprise data and AI capabilities that enable data-driven decisions, automation, and innovation. This role independently designs, builds, and maintains data and AI systems that make data discoverable, reliable, and actionable across the organization. As a core member of the Digital Technology team, the Data & AI Engineer transforms data requirements into scalable pipelines and services, ensures the integrity and quality of data products, and contributes to the continuous improvement of Amtrak’s data and AI ecosystem. This position partners closely with platform, governance, and analytics teams to deliver trusted, production-ready data and insights.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
2–4 years of hands-on experience in data engineering, integration, or software development.
Proficiency in Python and SQL with strong foundations in data and AI architecture, including feature pipelines, model serving, and inference patterns.
Understanding of ETL/ELT concepts, APIs, and data pipeline orchestration.
Strong experience building federated data and feature models; performance tuning for analytics and AI workloads; designing reusable views and features; implementing caching, row-level security, and data contracts.
Experience working within cloud or hybrid data environments.
Strong analytical, debugging, and problem-solving skills.
Demonstrated ability to work independently and deliver high-quality results within an agile framework.
Effective collaboration and communication skills across technical and business stakeholders.

Nice To Haves

Experience with data lakehouse or cloud data platforms.
Familiarity with metadata management, lineage, and observability practices.
Exposure to AI/ML pipeline development, automation frameworks, or MLOps concepts.

Responsibilities

Design, develop, and maintain data pipelines, AI frameworks and integration workflows supporting analytics and AI applications.
Implement data transformation, validation, and quality controls to ensure reliability and compliance with standards.
Collaborate with architects, analysts, and data scientists to operationalize data models and business logic.
Participate in agile planning, sprint delivery, and retrospectives to continuously improve team performance.
Document technical specifications, lineage, and best practices for data assets and workflows.