Data Engineer

About the position: 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. 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.

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. * 3-5 years experience · 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