Data Platform Engineer (w/m/d)

About WEFRA LIFE

WEFRA LIFE is one of the leading advertising agencies in the healthcare sector. We are owner-managed, have been on the market for 90 years, and currently employ around 180 experts.

Your Company

• Partnership: We value long-term collaboration. Our employment contracts are unlimited.
• Teamwork: We work interdisciplinarily with strategists, PR professionals, creatives, data scientists, and other specialists. We foster team spirit with flat hierarchies.
• Work Environment: We prioritize your work-life balance with flexible working time models and mobile office options.
• Career Development: We offer attractive on-the-job development opportunities, workshops, and coaching.
• Sustainability: We offer the Deutschlandticket or a Job-Rad. Parking with EV charging stations is also available.
• Catering: Free water, coffee, tea, and fruit are provided. Our in-house cafeteria offers diverse lunch options.

Your Team

Our WEFRA LIFE INNOVATION HUB is an international team of experts in Data Analytics, IT, and Business Innovation. The Data Analytics team specializes in collecting, processing, and analyzing complex data to provide valuable insights and enable data-driven decisions. We support digitalization and progress within WEFRA LIFE and the healthcare industry.

Your Job

We are looking for a Data Platform Engineer (m/f/d) with strong Python and software engineering skills to design, build, and operate our data platform on Azure. This role sits at the intersection of Data Engineering and Software Engineering. You will develop scalable data pipelines and backend services, as well as internal tools that make data products usable for analytics and data science. The focus is on platform thinking, clean software architecture, and reusable systems, rather than traditional ETL processes.

What makes this role special:

• Combination of data pipelines and backend systems
• Development of data products and APIs instead of pure ETL
• Active design of a scalable data platform
• Use of software engineering best practices (Testing, CI/CD, Architecture)
• Enablement of self-service analytics and data science

Your Tasks in Detail

• Design, build, and operate scalable data pipelines and a robust data platform on Azure with Databricks.
• Develop batch and near-real-time data processing with Python and SQL and integrate external data sources and APIs.
• Model data for analytics, data science, and data-driven applications, ensuring data quality, testing, monitoring, and observability.
• Develop production-ready Python backend services, APIs, and internal tools to make data and metrics usable for business units.
• Undertake data science enablement, e.g., through feature pipelines, training datasets, and support for model deployments.
• Take responsibility for deployment and operation of data services, including containerization, CI/CD, logging, and monitoring.