PySpark Data Engineer

BraverIT; Kraków; Hybrid; PLN 180,000 - 240,000; Full time

Job summary

BraverIT is seeking 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 reliable pipelines for business use cases.

You will design, build, and maintain data pipelines, transform data workflows, and ingest data from multiple cloud sources while ensuring performance and data quality. Collaboration with stakeholders and continuous process improvement are key aspects of this role.

Qualifications

• Minimum 3 years of experience in Data Engineering.
• 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 with Delta Lake, 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.

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.

Skills

PySpark

Databricks

Azure Data Factory

Azure SQL

Delta Lake

Parquet/CSV formats

CI/CD

English proficiency

Power BI

Tools

Databricks

Power BI

Job description

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