Middle Databricks Developer with Azure, Data Platform
About the Position
We are looking for a Strong Middle / Senior Databricks Developer with Azure to build scalable data platforms, develop complex data pipelines, and support cloud based data engineering solutions.
About the Project
The Data Platform project focuses on delivering cloud based data engineering solutions in the Microsoft Azure ecosystem. You will work with Databricks, Spark, and Azure services to build and optimize reliable data pipelines and support modern Lakehouse architecture.
About the Team
DataArt's team in this project consists of 8 people who constantly interact with the technical team on the client side which consists of 20+ technical specialists. The work is SCRUM-based with weekly sprints.
Responsibilities
- Design data solutions using Databricks
- Develop data pipelines for structured and unstructured data
- Build ETL and ELT workflows in Azure
- Develop high performance solutions using PySpark and Spark SQL
- Design Lakehouse architectures using Delta Lake
- Integrate data from databases APIs cloud services and streaming platforms
- Optimize Spark workloads for performance scalability and cost efficiency
- Ensure data quality governance security and monitoring standards
- Collaborate with Data Engineers Data Architects Analytics teams and business stakeholders
- Participate in architectural discussions and technical decision making
- Support CI and CD processes and infrastructure automation practices
Requirements
- 4+ years of experience in Data Engineering
- 3+ years of hands on experience with Azure Databricks
- Experience with Apache Spark and PySpark
- Knowledge of Python and SQL
- Experience with Azure Data Factory
- Experience with Azure Data Lake Storage Gen2
- Experience with Delta Lake and Lakehouse architecture
- Experience implementing end to end data pipelines in Azure
- Understanding of data modeling principles and best practices
- Experience working with large scale datasets in cloud environments
- Experience with Git based version control systems
- Upper Intermediate or higher English level
Nice to Have
- Experience optimizing Spark workloads
- Experience collaborating with cross functional technical and business teams
- Experience supporting CI and CD processes
- Experience with infrastructure automation practices
Technologies
Azure Databricks, Microsoft Azure, Apache Spark, PySpark, Spark SQL, Python, SQL, Azure Data Factory, Azure Data Lake Storage Gen2, Delta Lake, Lakehouse architecture, Git
