Data & AI Delivery Lead – Enterprise Asset Management (EAM)

ZipStaff Inc.; Washington (District of Columbia); On-site; USD 150,000 - 200,000; Full time

Job summary

ZipStaff Inc. is seeking a Data & AI Delivery Lead to drive end-to-end execution of analytics, AI/GenAI solutions, and data pipelines on the Databricks Lakehouse for a major rail and transit organization in Washington, DC.

You will own architecture, governance, and integration with reliability teams to modernize asset management and maintenance planning. You will lead development of predictive models, health indicators, and lifecycle cost analyses while coordinating with engineering,

Qualifications

• 7+ years of progressive experience in data engineering, advanced analytics, or asset analytics.
• 3+ years of project or program management experience leading complex enterprise data or asset-management solutions.
• Hands-on Databricks Lakehouse experience, including Medallion Architecture, Unity Catalog, and modern AI/ML tooling.
• Deep familiarity with reliability engineering, condition monitoring, predictive maintenance, or enterprise asset management concepts.

Responsibilities

• Oversee end-to-end delivery of analytics, machine learning, predictive modeling, and GenAI use cases on the enterprise Databricks platform.
• Build and optimize pipelines using Databricks Workflows and Medallion Architecture to ingest sensor feeds, inspection records, maintenance histories, and operational/financial datasets.
• Guide development of predictive health models, failure-probability algorithms, Remaining Useful Life (RUL) indicators, and financial lifecycle cost models.
• Implement enterprise data governance, lineage, and security using Unity Catalog.
• Evaluate and integrate modern Databricks features (Delta Live Tables, MLflow, Vector Search).
• Partner with engineering, reliability, and operations teams to deploy dashboards and risk-scoring frameworks aligned with ISO 55000 and regulatory requirements.
• Bridge executive business strategy and technical execution during high-demand project phases.

Skills

Databricks Lakehouse

Medallion Architecture

Unity Catalog

MLflow

Delta Live Tables

GenAI/AI tooling

Leadership/PM

Data governance

Tools

Databricks

Unity Catalog

Job description

Job Title: Data & AI Delivery Lead – Enterprise Asset Management (EAM)

Location: Washington, DC (On-site)

Employment Type: Contract (W2 through ZipStaff )

About the Opportunity

ZipStaff is seeking a Data & AI Delivery Lead to drive end-to-end execution of advanced data, analytics, and AI/GenAI solutions for a major rail and transit organization in Washington, DC.

You will be the primary technical leader owning the Databricks Lakehouse architecture used to modernize infrastructure asset management, condition monitoring, and long-term capital planning. The goal is to move traditional fixed-interval maintenance toward predictive, risk-based interventions.

What You’ll Do:

• Oversee end-to-end delivery of analytics, machine learning, predictive modeling, and GenAI use cases on the enterprise Databricks platform.
• Build and optimize pipelines using Databricks Workflows and Medallion Architecture to ingest sensor feeds, inspection records, maintenance histories, and operational/financial datasets.
• Guide development of predictive health models, failure-probability algorithms, Remaining Useful Life (RUL) indicators, and financial lifecycle cost models.
• Implement enterprise data governance, lineage, and security using Unity Catalog.
• Evaluate and integrate modern Databricks features (Delta Live Tables, MLflow, Vector Search).
• Partner with engineering, reliability, and operations teams to deploy dashboards and risk-scoring frameworks aligned with ISO 55000 and regulatory requirements.
• Bridge executive business strategy and technical execution during high-demand project phases.

Required Qualifications:

• 7+ years of progressive experience in data engineering, advanced analytics, or asset analytics.
• 3+ years of project or program management experience leading complex enterprise data or asset-management solutions.
• Hands-on Databricks Lakehouse experience, including Medallion Architecture, Unity Catalog, and modern AI/ML tooling.
• Deep familiarity with reliability engineering, condition monitoring, predictive maintenance, or enterprise asset management concepts.
• Ability to work on-site in Washington, DC.
• Must be legally authorized to work in the United States without sponsorship now or in the future.

Preferred Qualifications:

• Direct experience with rail infrastructure, transit networks, or linear assets.
• Databricks Certified Data Engineer (Professional) or Databricks Certified Machine Learning (Associate/Professional).