Data Engineer|Hybrid

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.
• Proven experience (7+ years) 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.

Job Description

Responsibilities include, but are not limited to, the following:

• 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.