Data Engineer

As a Data Engineer, you will build and maintain data products on a modern Databricks platform. You will work with data science & engineering teams to deliver reliable datasets used in AI solutions, reporting, analytics. Your focus will be on developing and operating data pipelines, data models and platform capabilities that make data easy to find, trust and use.

• Build and maintain data pipelines using Databricks and PySpark.
• Develop data products using modern Databricks capabilities such as Unity Catalog, Apache Spark™ Declarative Pipelines and Delta Lake.
• Create and improve data models that support reporting, self-service analytics and data science projects.
• Monitor pipeline health, troubleshoot issues and improve reliability, performance and cost efficiency.
• Work with analysts, data scientists and business stakeholders to understand requirements and deliver practical data solutions.
• Help establish data standards, data quality controls and governance practices across the platform.
• Contribute to the continuous improvement of the Databricks environment and engineering ways of working.

• Qualification: A degree in Computer Science, Software Engineering, Data Engineering or a related field.
• Experience: At least 3 years of hands-on experience building and maintaining data pipelines and data solutions.
• Technical skills: Strong Python skills. Experience with Databricks, PySpark, Delta Lake and Azure. Familiarity with Unity Catalog, data modelling and automated data processing workflows is a plus.
• Platform operations: Experience monitoring data pipelines, investigating failures and improving reliability and performance.
• Nice to have: Experience with Apache Spark™ Declarative Pipelines, CI/CD, DataOps practices (including Declarative Automation Bundles).
• Working style: You take ownership, communicate clearly and enjoy solving data engineering problems together with others.
• Languages: English at B2 level or higher.