Data Engineer

Ampstek; Warszawa; On-site; PLN 180,000 - 240,000; Full time

Job summary

Ampstek in Poland is seeking an experienced Data Engineer to design, build, and support scalable data platforms, ensuring reliable operations and data quality across complex environments.

You will work hands-on with Azure, Databricks, PySpark, Python and SQL, collaborating with engineers, analysts and business stakeholders in an Agile setting to deliver robust data solutions.

The role requires ownership of end-to-end pipelines and a proactive approach to performance, governance and security.

Qualifications

• 6+ years of professional Data Engineering experience.
• Strong hands-on experience with Microsoft Azure.
• Strong Databricks and PySpark experience.
• Strong Python programming skills.
• Strong knowledge of SQL.
• Experience with SQL Server or Netezza.
• Experience with at least three of Power BI, Python, MongoDB, ETL/ELT, diverse data sources, and Agile processes.

Responsibilities

• Design, develop, and maintain scalable data engineering solutions.
• Develop and optimise data pipelines using Azure and Databricks.
• Work hands-on with Databricks and PySpark for data processing and transformation.
• Develop data solutions using Python, SQL, and Spark.
• Build and maintain ETL/ELT pipelines and data workflows.
• Troubleshoot and resolve data quality, maintenance, and production issues.
• Collaborate with data engineers, developers, analysts, architects, and business stakeholders.
• Participate in Agile/Scrum ceremonies and follow data-driven development practices.
• Contribute to continuous improvement, automation, reliability, and performance optimisation.
• Ensure solutions follow appropriate security, governance, and data-quality standards.
• Take ownership of assigned tasks and deliver solutions within agreed timelines.

Skills

Data engineering

Azure

Databricks

PySpark

Python

SQL

SQL Server

ETL/ELT

Agile/Scrum

Tools

Power BI

MongoDB

Netezza

Job description

We are looking for an experienced Data Engineer to join our team in Poland. The successful candidate will be responsible for developing and supporting data engineering solutions, resolving maintenance and data-quality issues, and ensuring the efficient and reliable operation of data platforms and systems.

The ideal candidate will have strong hands-on experience with Microsoft Azure, Databricks, PySpark, Python, and SQL, along with the ability to work effectively in a complex and rapidly changing data environment.

Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions.
• Develop and optimise data pipelines using Azure and Databricks.
• Work hands-on with Databricks and PySpark for data processing and transformation.
• Develop data solutions using Python, SQL, and Spark.
• Build and maintain ETL/ELT pipelines and data workflows.
• Troubleshoot and resolve data quality, maintenance, and production issues.
• Work with diverse and complex data sources and ensure data accuracy and reliability.
• Develop and optimise SQL queries and database operations.
• Support internal users and business processes by delivering reliable data solutions.
• Collaborate with data engineers, developers, analysts, architects, and business stakeholders.
• Participate in Agile/Scrum ceremonies and follow data-driven development practices.
• Contribute to continuous improvement, automation, reliability, and performance optimisation.
• Ensure solutions follow appropriate security, governance, and data-quality standards.
• Take ownership of assigned tasks and deliver solutions within agreed timelines.

Mandatory Skills

• 6+ years of professional Data Engineering experience.
• Strong hands-on experience with Microsoft Azure.
• Strong hands-on experience with Databricks and PySpark.
• Strong programming skills in Python.
• Strong knowledge of SQL.
• Experience with SQL Server or Netezza.
• Experience with at least three of the following:
• Power BI
• Python
• MongoDB
• Strong understanding of ETL/ELT and data pipelines.
• Experience working with multiple and complex data sources.
• Good understanding of Agile software development processes.