Data Engineer
hace 2 días
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 keep our data solutions 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 high proficiency in programming fundamentals. At least two 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 efficiently (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; 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. Seniority level Entry level Employment type Full‑time Job function Information Technology Industries Oil and Gas #J-18808-Ljbffr
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