Junior Data Engineer — Azure Databricks & Lakehouse

Miratech; Warszawa; On-site; PLN 60,000 - 90,000; Full time

Benefits offered by this job

Health insurance

Language courses

Relocation program

Remote work culture

Job summary

Miratech is seeking a Junior Data Engineer specialized in Azure Databricks to join our data platform team. You will develop and support modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory, integrating with SQL Server-based data warehouses to empower analytics.

You will evolve ETL/ELT processes, optimize transformations with PySpark/SQL, and collaborate with BI teams on Power BI solutions, while learning within a cloud-native data ecosystem.

Qualifications

• 2+ years of experience in Data Engineering or related field.
• Experience with Azure Databricks and Spark-based pipelines.
• Strong SQL skills and experience with SQL Server.

Responsibilities

• Support and evolve existing SQL Server data platforms and ETL solutions.
• Build and optimize data transformations using PySpark and SQL in Databricks.
• Develop ETL/ELT pipelines orchestrated through Azure Data Factory.
• Integrate data from multiple sources into the data platform and analytics layers.
• Maintain data models and data warehouse structures for analytics.
• Ensure data quality, scalability and performance of large-scale pipelines.
• Collaborate with BI teams to support Power BI and reporting.

Skills

Azure Databricks

PySpark

Spark SQL

SQL Server

Big data concepts

SQL

Tools

Azure Data Factory

Databricks

Power BI

Job description

Miratech is seeking a Junior Data Engineer specialized in Azure Databricks to join our data platform team. You will develop and support modern data pipelines and Lakehouse architectures using Azure Databricks, Spark, and Azure Data Factory, integrating with SQL Server-based data warehouses to empower analytics.

You will evolve ETL/ELT processes, optimize transformations with PySpark/SQL, and collaborate with BI teams on Power BI solutions, while learning within a cloud-native data ecosystem.