Data & AI Delivery Lead || Washington, DC || Local Candidates Only

We are seeking a high-caliber Data & AI Delivery Lead Enterprise Asset Management (EAM) to drive the end-to-end execution of advanced data, analytics, and AI/GenAI solutions. This role operates at the intersection of business strategy, program delivery, and hands-on technical execution. The successful candidate will serve as the primary technical leader responsible for Databricks Lakehouse architecture supporting infrastructure asset management, condition monitoring, and long-term capital planning. Key Responsibilities

• Lead end-to-end delivery of analytics, machine learning, predictive modeling, and GenAI use cases on the enterprise Databricks platform.
• Design, build, and optimize scalable data pipelines using Databricks Workflows and Medallion Architecture .
• Ingest, process, and curate complex datasets including sensor feeds, inspection records, maintenance histories, and operational/financial data.
• Guide development of predictive asset health models, failure probability algorithms, and Remaining Useful Life (RUL) indicators.
• Support financial lifecycle cost modeling and risk-based capital allocation.
• Implement enterprise data governance, lineage, and security standards using Unity Catalog .
• Evaluate and integrate modern Databricks capabilities including Delta Live Tables, MLflow, and Vector Search .
• Partner with engineering, reliability, and operations teams to deliver interactive dashboards and risk-scoring frameworks.
• Align solutions with industry standards such as ISO 55000 and applicable regulatory requirements.
• Lead cross-functional teams through complex enterprise data and AI initiatives.
• Bridge executive business strategy and technical execution during critical project phases.
• Drive productivity, resolve technical challenges, and maintain project momentum.

• 7+ years of progressive experience in data engineering, advanced data analytics, or asset analytics.
• 3+ years of project or program management experience leading complex enterprise data initiatives or asset management solutions.
• Strong hands-on experience with the Databricks Lakehouse ecosystem .
• Proven experience with: Databricks Medallion Architecture Unity Catalog Databricks Workflows AI/ML tooling Data pipelines and analytics
• Deep knowledge of: Reliability engineering Condition monitoring Predictive maintenance Enterprise Asset Management (EAM)
• Strong technical leadership and program delivery experience.
• Excellent communication and stakeholder management skills.

• Direct experience with rail infrastructure, transit networks, or linear assets .
• Databricks Certified Data Engineer Professional certification.
• Databricks Certified Machine Learning Associate/Professional certification.
• Experience with predictive asset health, failure prediction, or Remaining Useful Life (RUL) modeling.
• Experience implementing enterprise data governance and security frameworks.
• Experience working with engineering, reliability, operations, and asset management stakeholders.

For applications and inquiries, contact:View email address on us.fitly.work