This job has closed.

Energy Job Search · 1 day ago

Data Engineer - Enterprise AI

Houston, TX

Full-time

Onsite

Senior Level

5+ years exp

Chevron is seeking a Data Engineer to join their Enterprise AI team, focusing on building intelligent data solutions for advanced analytics and AI-driven decision-making. The role involves designing and implementing scalable data and AI solutions, deploying automated data transformation pipelines, and collaborating with cross-disciplinary teams to ensure data quality and interoperability across multiple AI applications.

Staffing & Recruiting

No H1B

Responsibilities

Architect and Optimize Data Pipelines: Design, develop, and maintain robust ETL/ELT pipelines leveraging Databricks (including Databricks Genie for AI-assisted development), Azure Data Factory, Azure Synapse, and Azure Fabric. Architect solutions with a holistic AI foundation, ensuring pipelines and frameworks are built to support agentic AI systems, machine learning, and generative AI at scale

Enable AI-Ready Data: Build modular, reusable data assets and products optimized for AI workloads, ensuring data quality, lineage, governance, and interoperability across multiple AI applications

Collaborate Across Disciplines: Partner with AI delivery teams, including software engineers, AI engineers, and applied scientists, to deliver AI-ready datasets and features that accelerate model development and deployment

Performance and Scalability: Optimize pipelines for big data processing using Spark, Delta Lake, and Databricks-native capabilities, ensuring scalability and reliability for enterprise-scale AI workloads

Cloud-Native Engineering: Implement best practices for CI/CD, infrastructure-as-code, and DevOps using Azure DevOps, Git, and Ansible, while integrating with Databricks workflows for seamless deployment and reuse

Innovation and Continuous Learning: Stay ahead of emerging technologies in data engineering, AI/ML, and cloud ecosystems, leveraging AI tools like Databricks Genie and Agent Bricks and emerging tools and services within Azure AI Foundry and Fabric to accelerate development and maintain cutting-edge, reusable solutions

Qualification

DatabricksAzure Data FactoryETL/ELT processesPythonData modelingData governanceCI/CDSparkCollaboration skillsProblem-solving skillsAttention to detail

Required

Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience) and able to demonstrate high proficiency in programming fundamentals

At least 5 years of proven experience as a Data Engineer or similar role dealing with data and ETL processes in cloud-based data platforms (Azure preferred)

Strong hands-on experience with Databricks (Lakehouse, Delta Lake, Unity Catalog) and Microsoft Azure services (Azure Data Factory, Azure Synapse, Azure Blob Storage and Azure Data Lake Gen 2)

Strong understanding data modeling, data governance, and software engineering principles and how they apply to data engineering (e.g., CI/CD, version control, testing)

Strong problem-solving skills and attention to detail

Excellent communication and collaboration skills