Lead Data and AI Architect

Job Purpose

The Data & AI Lead plays a critical role in shaping the refinery’s digital future through modern data architecture, advanced analytics, and AI/ML adoption. This role will design, implement, and govern enterprise data platforms, AI strategy, and data governance frameworks to support reliable, efficient, and safe refinery operations. He Data and Ai Architect is a key contributor to the Deer Park Refinery Digital Transformation roadmap development and implementation. 

Dimensions

• Key technical leadership role within the IT Digital Transformation Team
• Supports enterprise-wide data governance, AI enablement, and analytics capability
• Partners with Business Owners, Enterprise Architects, Data Leads, PMO, and fusion teams

Accountabilities & Responsibilities:

The Data & AI Lead is responsible for developing and executing a site‑wide data, analytics, and AI transformation strategy that supports the refinery’s business goals and operational objectives. This includes identifying emerging data and AI technologies, evaluating high‑value opportunities, and creating business cases and ROI analyses that demonstrate the value of proposed solutions. The role will lead proof of concept (POCs), develop scalable solution patterns, and transfer knowledge to IT project teams to ensure successful deployment of new technologies that enhance efficiency, safety, reliability, and sustainability. Additionally, Data & AI Lead will define the data and analytics application roadmap, establish overarching enterprise data architecture, and create methods and frameworks to drive user adoption and organizational change.

Data & AI Strategy

• Develop and maintain the refinery’s Data & AI strategy and multi‑year digital transformation roadmap
• Identify and evaluate new AI, analytics, and data engineering technologies relevant to complex industrial environments
• Define enterprise standards for data architecture, modeling, governance, and AI/ML lifecycle management
• Drive alignment with refinery architecture, cybersecurity, and OT/IT integration strategies

Data Architecture & Engineering

• Architect scalable, secure, and cost‑efficient Azure cloud data platforms (Data Lake, Fabric, Databricks, etc.)
• Design end‑to‑end pipelines integrating data from refinery OT systems (DCS, SCADA, historians), SAP, EAM, LIMS, and other operational systems
• Build conceptual, logical, and physical data models supporting operations, reliability, maintenance, and financial use cases
• Implement best practices for data ingestion, ELT/ETL, data observability, security, roles/permissions, data quality, and metadata management

AI/ML Enablement

• Define AI/ML standards, model lifecycle governance, and responsible AI practices
• Partner with business teams to identify high‑value AI opportunities (predictive maintenance, optimization, anomaly detection, etc.)
• Provide hands‑on leadership in deploying AI/ML models using Azure ML, Foundry, notebooks, and industrial data sources

Data Governance & Compliance

• Establish and lead site-wide data governance frameworks, policies, and stewardship roles
• Ensure compliance with privacy, operational integrity, cybersecurity, and regulatory requirements
• Develop and maintain data catalogs, lineage, and master/reference data structures

Collaboration & Leadership

• Mentor and guide Transformation Analysts, Data Leads, and business data owners
• Partner with PMO to develop business cases, ROI analyses, solution evaluation, and vendor selection
• Facilitate workshops, training, and change management activities to increase digital and data literacy‑management activities to increase digital and data literacy
• Communicate technical concepts to non‑technical audiences and promote data‑driven decision making

Value Generation & Protection

• Ensure data platforms and AI solutions are reliable, scalable, cost‑optimized, and aligned with refinery priorities
• Drive continuous improvement through analytics insights, automation, and performance optimization initiatives
• Support safe and efficient refinery operations through trusted, accurate, and timely data