Senior Data Engineer

About the role

Zühlke is internationally recognized for expertise in developing Data Platforms and data-driven solutions for customers in many different industries. We are investing heavily in global growth in AI & Data. We believe that Data will have a positive impact on our society and environment. Data allows us to address urgent yet unsolved problems in a broad range of fields, from specific applications within organisations to problems of global significance. As a Data Engineer, you will play a central role in designing, implementing, and maintaining robust data pipelines, ensuring they are both technically excellent and business-driven. With strong hands-on Python engineering skills, you will translate complex requirements into scalable, reproducible solutions that empower our clients with actionable insights. How you'll make impact - Serve as a trusted advisor, guiding clients towards effective technical solutions to their data challenges. - Design, develop, and optimize distributed data processing pipelines, with Python at the core. - Apply software engineering best practices in Python-including testing, modularity, code reviews, and documentation-to build maintainable solutions. - Create high-quality, reproducible datasets from diverse data sources in a scalable way. - Collaborate seamlessly with Architects, Software Engineers, and Data Scientists to deliver integrated solutions. - Understand the requirements of different producers and consumers of data services, tailoring outputs to their needs. - Deliver iteratively in an Agile environment, ensuring value from data is realized early and often. - Stay sharp technically, continuously learning and applying new concepts and technologies. What's important to us - You have a university degree in computer science, software engineering, data science or a comparable education. - At least 5 years in data or software engineering positions, with a focus on cloud-native data services. - Experience with variety of approaches to data architectures (e.g. Data Lake, Data Mesh, Data Warehouse, ETL pro-cessing) - Experience building robust event driven ETL solutions on AWS using Spark within Glue to handle large-scale datasets. - Practical data programming skills in Python and SQL. - Orchestrating workflows using Step function, Airflow. - Experience in Data modelling, performance monitoring and optimization. - Hands-on experience architecting scalable data solutions across AWS Redshift, Postgres, relational, and NoSQL data-bases. - Optimizing for both real-time operational transactions (OLTP) and complex analytical processing (OLAP). - Familiarity with big data infrastructures and concepts for storing and processing large and/or heterogeneous data vol-umes. - Practical knowledge of handling varied types of structured and unstructured data (text, tabular, graph, time-series, geo-spatial, image, etc.). - Experience with managing project timelines, risks, and deliverables, alongside strong stakeholder management skills to facilitate clear communication, expectation setting, and decision‑making. - Experience with agile development and DevOps methodologies. - Strong written and verbal communication skills, with the ability to clearly articulate technical concepts and progress to both business and technical stakeholders. Fluency in English is required for this position.