PySpark Data Engineer
Summary
Builds and maintains scalable data pipelines using PySpark, Databricks, and Azure to process and transform data for reliable business insights.
We are looking for a Data Engineer to design and maintain modern data solutions built on Databricks, PySpark, and Microsoft Azure. The role focuses on developing scalable data platforms and supporting business use cases with reliable data pipelines.
Your responsibilities
- Design, build, and maintain scalable data pipelines
- Develop data processing and transformation workflows
- Support data ingestion from multiple sources into cloud environments
- Ensure performance, reliability, and data quality across solutions
- Collaborate with business and technical stakeholders to translate requirements into data solutions
- Contribute to documentation and continuous improvement of data processes
- Work in a distributed team environment, focusing on product and business goals
Our requirements
- Minimum 3 years of experience in Data Engineering
- Strong hands on experience with PySpark (DataFrames, SparkSQL optimization, partitioning)
- Practical experience with Databricks and Azure Data Factory
- Knowledge of Azure SQL and core Azure services (Storage Accounts, KeyVault, VNET, Application Gateway, Azure Portal)
- Experience working with Delta, Parquet, and CSV file formats
- Experience with CI/CD processes
- Ability to work independently and solve problems with minimal supervision
- Strong written and spoken English
- Experience with Power BI
What we offer
- Work on modern data solutions in Azure and Databricks environment
- Flexible working model and stable long term cooperation
- Exposure to international projects and stakeholders
- Support for professional growth and continuous learning