Join our Team

Chevron invests on its people to build technical and professional competencies through various training opportunities, development programs, mentoring/coaching engagements, and certification courses. All are applied through experiential learning and actual practice while solving real business problems, but in a safe, supportive, and "fail-fast" environment.

Technology will play a crucial role in unlocking ever cleaner and more affordable sources of energy. Chevron is seeking innovative, technology professionals with a desire to thrive in the global digital environment and help us lead the global energy transition. An IT career at Chevron offers you the opportunity to work in a technical environment with a global reach.We differentiate ourselves through the application of cutting-edge technology, and by taking a collaborative approach that includes in-house expertise, proprietary solutions, and strategic partnerships. We also offer flexible work schedules and very competitive benefits.

Data architects lead the design and implementation of data collection, storage, transformation, orchestration (movement) and consumption to achieve optimum value from data. They are the technical leaders within data delivery teams. They play a key role in modeling data for optimal reuse, interoperability, security and accessibility as well as in the design of efficient ingestion and transformation pipelines.  They ensure data accessibility through a performant, cost-effective consumption layer that supports use by citizen developers, data scientists, AI, and application integration.  And they instill trust through the employment of data quality frameworks and tools. The data architect at Chevron predominantly works within the Azure Data Analytics Platform, but they are not limited to it.  The architect is responsible for optimizing costs for delivering data.  They are also responsible for ensuring compliance to enterprise standards and are expected to contribute to the evolution of those standards resulting from changing technologies and best practices.

Responsibilities:

• Design and implement scalable, high-performance data architectures that meet business requirements.

• Model data for optimal reuse, interoperability, security and accessibility.

• Develop and maintain data flow diagrams, and data dictionaries.

• Collaborate with stakeholders to understand data needs and translate them into technical solutions.

• Ensure data accessibility through a performant, cost-effective consumption layer that supports use by citizen developers, data scientists, AI, and application integration. 

• Ensure data quality, integrity, and security across all data systems.

• Lead the design and implementation of data warehouses, data lakes, and other data storage solutions.

• Establish and enforce data governance policies and best practices.

• Ensure compliance to enterprise standards and contribute to the evolution of those standards resulting from changing technologies and best practices.

• Mentor and guide junior data engineers and analysts.

• Mentor other data architects.

• Influence and guide the evolution of data architecture standards across the enterprise.

Requirements:

• Proven experience as a Data Architect or similar role.

• Strong knowledge of data modeling, data warehousing, and data integration techniques.

• Proficiency in database management systems (e.g., SQL Server, Oracle, PostgreSQL).

• Experience with big data technologies (e.g., Hadoop, Spark) and data lake solutions (e.g., Azure Data Lake, AWS Lake Formation).

• Familiarity with cloud platforms (e.g., Microsoft Azure, AWS, Google Cloud Platform).

• Strong understanding of data governance and security best practices.

• Excellent problem-solving skills and attention to detail.

• Strong communication and collaboration skills.

• Bachelor’s degree in computer science, Information Technology, or a related field (or equivalent experience).

Preferred Qualifications:

• Experience in Erwin, Azure Synapse, Azure Databricks, Azure DevOps, SQL, Power BI, Spark, Python, R.

• Familiarity with Azure AI/ML Services, Azure Analytics: Event Hub, Azure Stream Analytics, Scripting: Ansible 

• Experience with machine learning and advanced analytics.

• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).

• Understanding of CI/CD pipelines and automated testing frameworks.