Data Engineer

Company DescriptionSika is a specialty chemicals company with a globally leading position in the development and production of systems and products for bonding, sealing, damping, reinforcing, and protection in the building sector and industry. Sika has subsidiaries in 103 countries around the world, produces in over 400 factories, and develops innovative technologies for customers worldwide. In doing so, it plays a crucial role in enabling the transformation of the construction and transportation industries toward greater environmental compatibility. In 2024, Sika’s around 33,000 employees generated annual sales of CHF 11. 76 billion.

Job DescriptionSika is expanding rapidly, and our data requirements are growing just as fast. To meet these needs, we are shaping a global strategy for how Sika manages and leverages analytical data, and we are building a state-of-the-art cloud-based data analytics platform. Join our Central Data & Analytics Team as a Data Engineer in Zürich, where you will play a pivotal role in designing and implementing innovative solutions for data engineering and analytics.

In this position, you will directly influence the architecture and execution of our new global data analytics approach, helping to set the standard for how Sika utilizes data to drive business value. Month 1-2What to expect in your first 6 MonthsGet to know the existing data architecture, technology stack, and key data sources (e. g. , SAP S/4Hana, Salesforce, SAP ByDesign, others). Deepen your understanding of our data mesh concept and its implementation. Build relationships with our team, data domain specialists, and stakeholders.

Begin making initial platform improvements and laying the groundwork for scalable ETL/ELT pipelinesMonth 3-4Design, build, and maintain production-grade ETL/ELT pipelines to load and transform data from enterprise systems (SAP S/4Hana, Salesforce, SAP ByDesign, others) into structured formats. Implement data transformation processes using tools like Azure Databricks, dbt and Azure Data Factory, ensuring alignment with business logic and analytics needs. Establish automated data quality checks, consistency monitoring, and validation frameworks to ensure reliable data availability. Month 5-onwardsCollaborate with domain specialists to deliver data products for analytics and AI use cases.

Fine-tune pipelines and data models for performance (query optimization, partitioning) and cost-efficiency (autoscaling, storage tiering). Develop reusable templates and documentation to enable domain teams to build their own ETL/ELT pipelines in alignment with global standards. Contribute to strategic decisions about platform evolution, including evaluation of new tools and architectural patterns. QualificationsA degree in Computer Science, Management of Information Systems, Data Science, or equivalent professional experience; Relevant certifications on Data Engineering are a plus. Several years of experience in Data Engineering or relevant role. Familiarity with domain-oriented data management approaches, such as Data Mesh.

Experience with Azure services such as Azure Databricks, Azure Data Factory, Storage Account, Key Vault. Coding experience with languages such as SQL, Python, PySpark, dbtExperience working with code versioning tools such as Azure DevOps or GitHub. Experienced with DevOps principles such as CI/CD pipelines and release processesFluency in English; proficiency in additional languages is a plus. Additional InformationThis position offers Hybrid working conditions and is subject to change at any time. Candidate is required to work in the Zürich office 4 days per week with 1 day being remote. This position does not offer Visa Sponsorship opportunities.

Friendly, personable and often surprisingly uncomplicated, that's how many of our employees describe their working relationships at Sika. We call this the Sika SpiritWe offer a fair employment package with good social benefitsWe look forward to your direct online application.