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 industrial manufacturing. Sika has subsidiaries in 103 countries around the world and, in over 400 factories, produces innovative technologies for customers worldwide. In doing so, it plays a crucial role in enabling the transformation of the construction and transportation sector toward greater environmental compatibility. With more than 33,000 employees, the company generated sales of CHF 11.20 billion in 2025.
About the Role
Sika is looking for a Data Engineer to join our Sustainability team and build the data foundation behind our global Scope 3 carbon accounting. This is a technical role for someone who enjoys turning complex data into reliable, scalable solutions-designing data models, building pipelines, implementing calculation logic, and solving data-quality challenges. You don’t need a sustainability background; what matters is your ability to understand data, uncover insights, and solve problems. You’ll help digitalize and automate our processes, strengthen analytics and decision-making, and contribute to Sika’s Net Zero journey. The initial focus is on data engineering, with growing ownership of analytics over time.
- Develop, maintain and improve scalable data pipelines, data models, transformation workflows, and calculation logic for Sika’s Scope 3 accounting framework.
- Support the migration of Scope 3 solutions from SAP BI Cubes to Databricks, translating existing business logic and data structures.
- Design and maintain analytical data warehouse and lakehouse solutions using dimensional modelling, medallion architecture,
- Simplify and automate data flows across multiple source systems and contribute to the team’s digitalization journey through AI and automation.
- Build automated validation, testing, and reconciliation controls to ensure high data quality and reliable, auditable calculation outputs.
- Investigate complex data issues, identify root causes, and ensure the technical and logical consistency of calculation results.
- Support strong data governance through clear ownership, documentation, lineage, Unity Catalog, and secure access controls.
- Contribute to CI/CD practices, including version control, automated testing, deployment, and release management across environments.
- Analyze complex data, support scenario modelling, and develop dashboards and reporting solutions that generate actionable insights for business decisions.
- Degree in Computer Science, Management of Information Systems, Data Science, or equivalent professional experience
- 2-3 years of experience in Data Engineering or a related field (software engineering, data science data analytics)
- Proven experience with data platforms like Databricks or similar (Snowflake, Microsoft Fabric, Google BigQuery or similar)
- Proven experience with Azure services including Data Factory, Storage Account, and Key Vault
- Coding skills in SQL, Python and PySpark
- Experience with code versioning and DevOps tools such as Azure DevOps or GitHub, and CI/CD practices
- Familiarity with data governance concepts and tools, including data management, data lineage, access controls, and row-level security, is an advantage
- Strong analytical, problem-solving, and communication skills
- Curious mindset and willingness to continuously learn
- Fluency in English; German and/or French are plus
Preferred
- Data Engineering certifications
- Dbt experience
We look forward to your application. For this position, only direct applications will be considered. For any further information please reach us at [email protected]
We offer competitive salaries, aligned with local market benchmarks and the specific scope and responsibilities of each role. Compensation is determined based skills relevant to the position, education and/or training. We are committed to fair and equitable pay practices in accordance with applicable laws and regulations.