champion the adoption
of emerging tech

Data Engineer:

Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.  A  Data Engineer designs data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective.  

Responsibilities:

• Design, develop, and maintain data pipelines and ETL processes using Microsoft Azure services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks, Azure Fabric).

• Utilize Azure data storage accounts for organizing and maintaining data pipeline outputs.  (e.g., Azure Data Lake Storage Gen 2 & Azure Blob storage).

• Collaborate with data scientists, data analysts, data architects and other stakeholders to understand data requirements and deliver high-quality data solutions.

• Optimize data pipelines in the Azure environment for performance, scalability, and reliability.

• Ensure data quality and integrity through data validation techniques and frameworks.

• Develop and maintain documentation for data processes, configurations, and best practices.

• Monitor and troubleshoot data pipeline issues to ensure timely resolution.

• Stay current with industry trends and emerging technologies to ensure our data solutions remain cutting-edge.

• Manage the CI/CD process for deploying and maintaining data solutions.

Requirements:

• 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 2 years of proven experience as a Data Engineer or similar role dealing with data and ETL processes.

• Strong knowledge of Microsoft Azure services, including Azure Data Factory, Azure Synapse, Azure Databricks, Azure Blob Storage and Azure Data Lake Gen 2.

• Experience utilizing SQL DML to query modern RDBMS in an efficient manner (e.g., SQL Server, PostgreSQL).

• Strong understanding of Software Engineering principles and how they apply to Data Engineering (e.g., CI/CD, version control, testing).

• Experience with big data technologies (e.g., Spark).

• Strong problem-solving skills and attention to detail.

• Excellent communication and collaboration skills.

Preferred Qualifications:

• Learning agility

• Technical Leadership

• Consulting and managing business needs

• Strong experience in Python is preferred but experience in other languages such as Scala, Java, C#, etc is accepted.

• Experience building spark applications utilizing PySpark.

• Experience with file formats such as Parquet, Delta, Avro.

• Experience efficiently querying API endpoints as a data source.

• Understanding of the Azure environment and related services such as subscriptions, resource groups, etc.

• Understanding of Git workflows in software development.

• Using Azure DevOps pipeline and repositories to deploy and maintain solutions.

• Understanding of Ansible and how to use it in Azure DevOps pipelines.

Relocation Options:

Relocation could be considered.

International Considerations:

Expatriate assignments will not be considered.

Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position

• d/or the deployment of technical services