Data Architect

Title: Data Architect (Databricks & Asset Analytics)
Remote role with Rail Industry based in Washington DC.
Duration: 12 months contract
Ideal candidate should have experience working with Capital projects and Asset Management.
Must have active Linkedin 2020 or before.
Strong Comm Skills
Snr folks 14+ yrs.
Rail and transportation industry exp pref first.
About The Role
The Data & AI Solutions Delivery Lead will drive the strategy, architecture, and end-to-end delivery of enterprise Data, Analytics, AI, and Business Intelligence solutions on the Databricks Lakehouse Platform. This role is heavily focused on Asset Analytics, enabling data-driven decision making for infrastructure asset management, reliability engineering, predictive maintenance, capital planning, and operational risk reduction.
The ideal candidate will combine deep expertise in Databricks, Data Engineering, and AI/ML with hands-on experience in asset-intensive industries such as rail, transportation, utilities, manufacturing, energy, or other linear asset environments. The individual will lead cross-functional teams in transforming operational, maintenance, inspection, and condition-monitoring data into actionable business intelligence and advanced predictive insights.
Key Responsibilities
Lead the design, development, and delivery of enterprise Data, Analytics, AI, and Business Intelligence solutions utilizing the Databricks Lakehouse Platform.
Architect and optimize scalable data pipelines leveraging Databricks Workflows, Delta Lake, Delta Live Tables, Unity Catalog, and Medallion Architecture.
Establish DevOps and CI/CD best practices through Databricks Asset Bundles (DAB), Git integration, deployment automation, and environment management.
Design and implement Asset Analytics solutions that provide deeper visibility into asset condition, reliability, performance, and lifecycle costs.
Develop advanced predictive analytics and machine learning models supporting:
Asset Health Monitoring
Failure Prediction & Root Cause Analysis
Remaining Useful Life (RUL) Estimation
Predictive & Prescriptive Maintenance
Reliability Centered Maintenance (RCM)
Critical Asset Risk Management
Asset Performance Optimization
Asset Lifecycle Forecasting
Build analytical frameworks that evaluate asset risk, maintenance effectiveness, asset criticality, and investment prioritization.
Develop risk-based models supporting capital planning, infrastructure investment strategies, asset replacement planning, and long-term maintenance programs.
Required Qualifications
7+ years of experience in Data Engineering, Data Analytics, Data Science, Asset Analytics, or Enterprise Data Platforms.
3+ years of experience leading large-scale Data, Analytics, AI, or Digital Transformation initiatives.
Strong hands-on experience with Databricks, Spark, Delta Lake, and modern cloud-native data platforms.
Experience delivering AI/ML, predictive analytics, business intelligence, and enterprise-scale reporting solutions.
Proven experience building asset health, reliability, maintenance, risk, or performance management analytics solutions.
Expertise in SQL, Python, PySpark, and modern data engineering practices.
Experience with cloud platforms such as Azure, AWS, or Google Cloud.
Required Skills
Databricks Lakehouse Platform, Data Engineering, Delta Lake & Medallion Architecture, Asset Analytics, Data Science & AI/ML, Predictive Maintenance, Reliability Engineering, Risk Analytics, PySpark & Python, SQL, Databricks Workflows, Unity Catalog, MLflow, Delta Live Tables, CI/CD & Databricks Asset Bundles (DAB)
Preferred Qualifications
Experience in rail, transportation, infrastructure, utilities, energy, manufacturing, or other asset-intensive industries.
Experience supporting linear asset environments such as rail networks, track infrastructure, roadways, pipelines, telecommunications, or utility transmission systems.
Strong knowledge of asset management frameworks including ISO 55000.
Experience with condition monitoring systems, IoT platforms, SCADA systems, telemetry, and sensor-based analytics.
Understanding of maintenance engineering methodologies including RCM, FMEA, Asset Criticality Analysis, and Risk-Based Maintenance.
Experience supporting capital planning, investment prioritization, and infrastructure lifecycle management programs.
Databricks Certifications
Databricks Certified Data Engineer Associate/Professional
Databricks Certified Machine Learning Associate/Professional
Databricks Certified Generative AI Engineer
Ideal Candidate Profile
The ideal candidate blends strong technical leadership in Databricks and AI/ML with deep knowledge of Asset Analytics, helping organizations optimize asset reliability, reduce maintenance costs, improve operational performance, extend asset lifecycles, and make data-driven capital investment decisions across large-scale infrastructure environments.

Work arrangement
Yes