Azure Data Engineer

We are looking for a Data Engineer who designs and oversees the data infrastructure, data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective.

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.

8-10 Years

:

• Oversee the 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.

• Manage the CI/CD process for deploying and maintaining data solutions.

:

• 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 8 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).

• Experience with big data technologies (e.g., Spark).

• Strong problem-solving skills and attention to detail.

• Excellent communication and collaboration skills.