Principal Data & AI Architect - Operations & Asset Analytics
Expert Technology Services
Job Summary (List Format): Principal Data & AI Architect Operations & Asset Analytics
- Lead the end-to-end delivery of enterprise data, advanced analytics, and AI/GenAI solutions within the rail and transportation operations sector.
- Serve as the technical authority for Databricks Lakehouse architecture, driving modernization of infrastructure asset management (EAM), condition monitoring, and capital planning.
- Architect, design, and deliver analytics, machine learning, predictive modeling, and GenAI use cases on the Databricks platform.
- Build, optimize, and oversee scalable data pipelines using Databricks Workflows and Medallion Architecture to process complex sensor, inspection, maintenance, and operational/financial data.
- Guide development of predictive health models, failure probability algorithms, Remaining Useful Life (RUL) indicators, and financial lifecycle cost models for risk-based decision making.
- Implement data governance, lineage, and security frameworks (Unity Catalog), and evaluate/integrate advanced Databricks features (Delta Live Tables, MLflow, Vector Search).
- Collaborate with cross-functional teams (engineering, reliability, asset management) to deploy interactive dashboards and risk-scoring frameworks aligned with industry standards and regulations (e.g., ISO 55000).
- Act as a technical anchor for EAM workstreams, bridging executive strategy and technical execution to minimize operational risk and project costs.
- Requires 7+ years of experience in data architecture, engineering, or asset analytics, and 3+ years in program/project leadership for complex enterprise data solutions.
- Strong hands-on experience with Databricks Lakehouse, Medallion Architecture, Unity Catalog, and ML/AI tools.
- Solid understanding of reliability engineering, condition-based monitoring, predictive maintenance, and EAM concepts.
- Preferred: Experience in rail infrastructure, transit, or linear assets; Databricks professional certifications.
- Lead the end-to-end delivery of enterprise data, advanced analytics, and AI/GenAI solutions within the rail and transportation operations sector.
- Serve as the technical authority for Databricks Lakehouse architecture, driving modernization of infrastructure asset management (EAM), condition monitoring, and capital planning.
- Architect, design, and deliver analytics, machine learning, predictive modeling, and GenAI use cases on the Databricks platform.
- Build, optimize, and oversee scalable data pipelines using Databricks Workflows and Medallion Architecture to process complex sensor, inspection, maintenance, and operational/financial data.
- Guide development of predictive health models, failure probability algorithms, Remaining Useful Life (RUL) indicators, and financial lifecycle cost models for risk-based decision making.
- Implement data governance, lineage, and security frameworks (Unity Catalog), and evaluate/integrate advanced Databricks features (Delta Live Tables, MLflow, Vector Search).
- Collaborate with cross-functional teams (engineering, reliability, asset management) to deploy interactive dashboards and risk-scoring frameworks aligned with industry standards and regulations (e.g., ISO 55000).
- Act as a technical anchor for EAM workstreams, bridging executive strategy and technical execution to minimize operational risk and project costs.
- Requires 7+ years of experience in data architecture, engineering, or asset analytics, and 3+ years in program/project leadership for complex enterprise data solutions.
- Strong hands-on experience with Databricks Lakehouse, Medallion Architecture, Unity Catalog, and ML/AI tools.
- Solid understanding of reliability engineering, condition-based monitoring, predictive maintenance, and EAM concepts.
- Preferred: Experience in rail infrastructure, transit, or linear assets; Databricks professional certifications.
Vacancy posted 1 day ago
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