SeniorFull TimeENEurope
Build, maintain, and support data pipelines ingesting data from operational systems, projects, and third-party sources.
Contribute to the design, development, and maintenance of data models.
Support the architecture and evolution of data solutions within the Data & Analytics landscape, in close collaboration with the Data Architect.
Document and maintain a clear picture of the data landscape, its sources, flows, models, and dependencies, as a joint initiative with the Data Architect.
Review and improve technical designs and implementations for consistency, quality, and scalability before they reach production.
Help define and continuously improve reporting and analytics standards.
Give the analytics team the right data structures, tools, and frameworks to do their best work.
Work cross-departmentally with business stakeholders, data scientists, and report developers to gather requirements and create value from data.
Work across both cloud-based and on-premise data architectures and technologies.
Extensive hands-on experience in data engineering, you have seen enough to know what good looks like and can back it up with examples.
Strong SQL skills and fluency in one or more data-oriented languages, Python, Scala, Spark, PySpark, or similar.
Solid experience designing and maintaining data pipelines for analytical and reporting use cases.
Solid data modelling skills, UML, ER modelling, analytical schemas.
Meaningful experience with Databricks and Unity Catalog as part of an analytical data platform.
Comfortable working within a Microsoft Azure–based data ecosystem.
Ability to think architecturally, understanding how pipelines, models, and platforms fit into a broader data landscape, and the ambition to be an active voice in shaping that landscape.
Hands-on and result-driven, you like to ship things and you hold yourself to a high bar.
Clear communicator, comfortable with both technical and non-technical stakeholders.
At ease in an agile environment and collaborative by nature.
Experience with different data types such as geospatial, time-series, structured and unstructured data; familiarity with BI tools like Power BI, Grafana, or Tableau; exposure to machine learning or advanced analytics; and a general curiosity and openness towards new technologies are a plus.
An extensive mobility program for a healthy work-life balance.
A permanent training track which allows you to develop yourself personally and professionally.
A stimulating, innovative workplace with numerous growth opportunities.
A people-oriented environment with an interactive health program and a focus on employee wellbeing.
