Join our team as a Technical Lead in Data Engineering, focusing on Databricks and PySpark.

This role involves designing, developing, and deploying robust data solutions within Azure services. You will be instrumental in building scalable data pipelines and integrating new data sources to manage growing data volumes and complexity.

We are seeking a candidate with a strong background in modern data warehousing and batch processing, capable of handling both structured and non-structured data. Your expertise will be crucial in collaborating with BI, analytics, and business teams.

Key responsibilities include performing design, development, and deployment using Azure services like Databricks, PySpark, SQL, and Data Factory.

You will develop and maintain scalable data pipelines, creating new data source integrations to support increasing data volume and complexity.

This role also involves creating technical specification designs, application interface designs, and developing modern data warehouse solutions utilizing the Azure stack (Azure Data Lake, Azure Databricks) with PySpark. You will develop batch processing and integration solutions, processing both structured and non-structured data.

A minimum of 2-3 years of project experience with Azure Databricks is required.

Additionally, a minimum of 2-3 years of experience with Azure Data Factory (ADF) and 2+ years of experience with PySpark are essential.

Demonstrated in-depth skills with Databricks, PySpark, and SQL are critical for success in this position. Collaboration with BI, analytics, and business teams is a key aspect of this role.