Mid Data Engineer

We are looking for a Mid Data Engineer with strong PySpark skills and basic hands-on experience with Databricks to join a data engineering project for an initial period of 3-6 months.

The role focuses on developing, maintaining and optimizing data pipelines, working with large datasets and supporting modern data processing solutions.

What you'll do

• Develop and maintain data pipelines using PySpark and Apache Spark.
• Build and optimize data transformation processes for large datasets.
• Integrate data from different sources and ensure reliable data processing.
• Write, maintain and optimize SQL queries.
• Work with Databricks to develop and execute data processing workloads.
• Troubleshoot pipeline issues and improve processing performance.
• Implement data quality checks and support reliable data delivery.
• Collaborate with other engineers and technical stakeholders on data engineering tasks.

Your experience

• Strong, hands-on experience with PySpark - this is the key requirement.
• Commercial experience in Data Engineering, ideally at a mid-level.
• Very good knowledge of SQL and data transformation techniques.
• Practical understanding of Apache Spark and distributed data processing.
• Basic hands-on experience with Databricks - you don't need to be an expert.
• Experience building and maintaining ETL/ELT data pipelines.
• Familiarity with cloud environments (Azure, AWS or GCP).
• Ability to work independently on assigned tasks and solve technical problems.

Nice to have

• Experience with Delta Lake.
• Familiarity with workflow orchestration tools.
• Knowledge of data quality and monitoring practices.
• Experience optimizing Spark jobs and working with large-scale datasets.
• Understanding of lakehouse architecture.

Tech stack

PySpark, Apache Spark, SQL, Databricks, Python

Additional technologies: Delta Lake, Azure / AWS / GCP.

Project details

• Position: Mid Data Engineer
• Project duration: 3-6 months
• Main focus: PySpark development and data pipeline engineering
• Databricks: Basic practical experience required

Why join?

You'll have the opportunity to work on a hands-on data engineering project, focusing on real-world PySpark development, data pipeline optimization and modern data processing technologies.

This is a great opportunity for an experienced PySpark developer who wants to further develop their skills while gaining additional exposure to Databricks.