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 Senior Data Engineer designs and oversees the entire data infrastructure, data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective. The expectation for this role is 5-10 years of relevant experience.
Key Responsibilities
Oversee the entire data infrastructure to ensure scalability, operation efficiency and resiliency.
Mentor junior data engineers within the organization.
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.
Required Qualifications
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. 5 - 10 years of experience
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.
Chevron ENGINE supports global operations, supporting business requirements across the world. Accordingly, the work hours for employees will be aligned to support business requirements. The standard work week will be Monday to Friday. Working hours are 8:00am to 5:00pm or 1.30pm to 10.30pm.
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