Assignment description

We are looking for a Senior Platform Engineer for an assignment within data platforms and pipelines.

The role focuses on developing and maintaining data platforms that make high-quality operational data accessible and valuable for analytics, data science and development.

The assignment has a strong focus on Databricks and data governance. You will take an active role in improving the Databricks platform setup, building scalable and reliable data pipelines, and strengthening governance capabilities across the data platform.

You will work closely with developers, Data Scientists, Machine Learning Engineers and business stakeholders to translate requirements into governed, secure and production-ready data products.

The assignment requires a high level of technical expertise, independence and the ability to contribute effectively from an early stage.

Key Responsibilities

• Design, develop, and maintain scalable data platforms and data pipelines with a strong focus on Databricks.
• Drive improvements to the existing Databricks platform setup, architecture, and capabilities.
• Develop and maintain robust ETL/data pipelines for large-scale operational data.
• Design and implement data governance models, catalogues, and metadata management capabilities.
• Ensure high standards for data quality, governance, discoverability, security, and compliance.
• Implement and manage Infrastructure as Code (IaC) solutions for Databricks and related cloud services.
• Enable automated, reliable, and reproducible infrastructure and platform environments.
• Design and implement technical solutions for complex data and platform challenges.
• Collaborate with developers, Data Scientists, Machine Learning Engineers, and business stakeholders.
• Translate technical and business requirements into governed and production-ready data products.
• Contribute to the continuous development, operation, and maintenance of the team’s data platform.

Qualifications:

• Degree in Computer Science, IT, Engineering, or equivalent relevant experience.
• Strong hands-on experience with Databricks and Spark.
• Strong experience with cloud-based data platforms, preferably AWS.
• Strong programming skills in Python and SQL.
• Experience designing and developing ETL/data pipelines.
• Experience with Infrastructure as Code (IaC) for Databricks and related cloud infrastructure.
• Strong understanding of data governance, data quality, metadata management, and data discoverability.
• Experience designing scalable, robust, and secure data platform solutions.
• AWS and/or Databricks certifications are considered a strong advantage.
• Several years of professional experience as a Data Engineer, Platform Engineer, or in a similar senior data engineering role.
• Proven hands-on experience working with Databricks in production environments.
• Experience designing, developing, and maintaining medium- to large-scale data platforms.
• Strong understanding of data platform architecture and modern data engineering practices.
• Experience implementing governance capabilities within complex data environments.
• Ability to independently drive technical improvements and solve complex platform and data challenges.
• Experience collaborating with both technical and business stakeholders.
• Strong analytical, communication, and problem-solving skills.
• Ability to translate requirements into scalable and production-ready technical solutions.

You are a senior and self-driven Data Engineer with strong hands-on expertise in Databricks and modern data platform development. You combine deep technical knowledge with a structured and pragmatic approach to solving complex problems.

You are comfortable taking ownership of technical solutions and driving improvements independently while collaborating closely with developers, Data Scientists, Machine Learning Engineers, and business stakeholders. You understand the importance of governance, data quality, security, and maintainability and have the ability to balance these requirements with the need to deliver scalable and valuable data products.