Azure Engineer Specialist

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 distribution of data types and volumes in support of data architecture design.

A Data Engineer designs data products and pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost-effective.

Key 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.

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, and 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.

Pyspark, Azure Data Factory (Adf), Azure Databricks (Adb), Delta Lakes, Adb