Data & AI Senior Engineer - 90405345 - Remote Job Details | Amtrak

Amtrak is a leading transportation company dedicated to connecting businesses and communities across the United States. They are seeking a Data & AI Senior Engineer to lead the design and delivery of complex data and AI solutions that enhance Amtrak's analytics and operational systems while mentoring junior engineers and influencing design decisions across teams.

Responsibilities:

• 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

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, or a related technical field; equivalent experience may be considered
• 4–6 years of experience in data engineering, software development, or data architecture
• 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, schema enforcement, lineage tracking, and policy-as-code controls directly into pipelines and AI workflows
• Excellent communication, collaboration, and problem-solving abilities
• Experience building reusable cost effective, feature stores, semantic layers, or internal platform services that enable self-service analytics and AI
• 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