Enterprise Data Architect for AI/Analytics Platform

HF Sinclair Corporation; Dallas (TX); Sur place; USD 150 000 - 210 000; Plein temps

Avantages offerts par ce poste

Medical Insurance

Vision Insurance

Dental Insurance

Paid Time-Off

401(k) Retirement Plan with match

Educational Reimbursement

Parental Bonding Time

Employee Discounts

Résumé du poste

HF Sinclair Corporation in Dallas, TX is seeking a Senior Data Architect to design and govern secure, scalable, reusable enterprise data architecture across the oil and gas value chain.

You will translate business and technical needs into target-state architectures spanning source systems, integration, data engineering, cloud platforms, governance, analytics, data products, and AI/ML, while partnering across multiple teams.

Qualifications

• 10+ years of experience in data architecture and related roles.
• Experience with data governance, metadata, lineage, and data products.
• Strong knowledge of data modeling, warehousing, and analytics platforms.

Responsabilités

• Define enterprise data principles, standards, and reference architectures.
• Architect data warehouses, lakes, lakehouses, and data products.
• Define architecture standards for AI/ML, MLOps, and feature engineering.
• Architect secure AI and generative AI solutions with foundation models and RAG.
• Establish reusable data services, ingestion, indexing, and semantic retrieval.
• Partner with cross-functional teams to operationalize AI solutions with governance.

Connaissances

Data architecture

Enterprise analytics

Cloud platforms

Governance

AI/ML concepts

MLOps/LLMOps

API-led integration

Stakeholder management

Documentation

Formation

Bachelor's degree in computer science / related field

Outils

Snowflake

Azure

Power BI

Streamlit

Qlik

Cognite

Description du poste

HF Sinclair Corporation in Dallas, TX is seeking a Senior Data Architect to design and govern secure, scalable, reusable enterprise data architecture across the oil and gas value chain.

You will translate business and technical needs into target-state architectures spanning source systems, integration, data engineering, cloud platforms, governance, analytics, data products, and AI/ML, while partnering across multiple teams.