Data Engineer

  • Das Bundesamt für Statistik BFS
  • Canton of Neuchâtel, Switzerland
  • 01/01/2022
Full time Data Engineering Business Intelligence Software Engineering Data Governance

Job Description

Statistics matters. For you too.
You are interested in the application of data science (“data science”) for the common good throughout Switzerland (“for public good”). You have mastered the tools for ETL and machine learning. You are interested in the life cycle of projects in the areas of data science, procurement and implementation of models as well as standards and metadata. In the past few years you have implemented projects in different areas that cover different sections of the data life cycle.

Your tasks

  • With a focus on “Data Engineering”, the service manager “Data & Methods Engineering” in the construction, maintenance and further development of the data science platforms of the Competence Center for Data Science (DSCC) with regard to the underlying architecture and ICT infrastructure, configurations of all tools and interfaces, Support data models and data integration processes (e.g. integration of source systems into the data science platforms of the DSCC) and the active design of innovative new approaches and processes
  • Responsibility for the merging and provision of structured and unstructured data sets with different data types and formats for the application of data-based data science methods, taking into account data sensitivity
  • Design, implement and monitor data pipelines, data feeds and data processing, both for real-time requirements and for batch processing, taking into account the existing data protection requirements. Design and develop scalable, error-resistant and high-performance data storage solutions
  • Develop, implement and maintain interfaces to databases and other applications. Create data, function and / or object models and their documentation. Provide support in the area of ​​data governance and security through design proposals for the access and authorization concept, auditing and monitoring. Optimize data processing pipelines in terms of performance, reliability and resource efficiency. The various data repositories of the DSCC including documentation, authorization management, monitoring, logging and alerting. Analyzes malfunctions and error states, manage and maintain, derive and monitor measures to rectify them
  • The data scientists of the “Data Science Engineering” service advise and support the application of a range of data engineering practices. Being able to develop in-depth specialist knowledge in a narrower range of specialist areas. Being able to translate technical needs into data-based data science issues. Apply emerging theory to practical situations

your profile

  • Master's degree (MSc) in the field of data science, computer science or a related subject, with a focus on data engineering. Proven experience (preferably at least 3 years) as a data engineer in the field of data science in a public administration, a university and / or in the private sector
  • Experience in carrying out data science projects as part of a continuous improvement cycle. Proven experience in the development, operationalization, implementation and monitoring of specific data-based use cases in the field of data science with corresponding product development
  • Pronounced business, analytical and conceptual thinking and acting as well as innovative creative drive. Affinity for engineering thinking
  • High advisory competence. Excellent communication, both in two official languages ​​and in English. Passive understanding of a third official language
  • In-depth experience with various programming and scripting languages, frameworks and tools (e.g. R, Python, Java, Scala, AirFlow, Bash, C #, Golang). Knowledge of scientific tools (e.g. Jupyter Notebooks). In-depth understanding and experience in the use of container technologies (e.g. Kubernetes), knowledge of cloud services (e.g. Apache Kafka, PostgreSQL, MinIO) and automation tools is an advantage. Proven experience in the application, development and maintenance of databases, programming interfaces, web technologies, ETL processes and other data-intensive applications. Very broad / deep specialist knowledge in the conception and implementation of data pipelines, and in the provision of data using "Big Data" technologies (e.g. Spark, Kafka, Nifi, Hive, Object Stores, Hadoop Ecosystem). Proven experience with versioning and deployment tools and with “Continuous Integration and Continuous Delivery” (CD / CD) pipelines (e.g. Git, GitLab CI / CD, Jenkins). Expert knowledge of agile development processes (DevOps)

Additional Information

For further information, please contact Christine Choirat, Head of Section, +41 (0) 58 481 95 09
The position is limited to December 31, 2024.
Internal reference: DSde2112Reference number: 48332