Senior Data Engineer

Sika 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.

Sika 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 Senior Data Engineer, 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.
 

What to expect in your first 6 Months

Month 1-2:

• Get 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 pipelines

Month 3-4:

• Design, 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-onwards:

• Collaborate 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.

• A 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, dbt
• Experience working with code versioning tools such as Azure DevOps or GitHub.
• Experienced with DevOps principles such as CI/CD pipelines and release processes
• Fluency in English; proficiency in additional languages is a plus.

Friendly, personable and often surprisingly uncomplicated, that's how many of our employees describe their working relationships at Sika. We call this the Sika Spirit

We offer a fair employment package with good social benefits

We look forward to your direct online application.