Data Engineer - Sustainability (Scope 3 Carbon Accounting)

About the role

Sika is looking for a Data Engineer to join its Sustainability team and build the data foundation behind its global Scope 3 carbon accounting. The role turns complex data into reliable, scalable solutions: designing data models, building pipelines, implementing calculation logic and solving data-quality challenges. It is a technical role with no sustainability background required, and the initial focus is on data engineering, with growing ownership of analytics over time.

Key responsibilities

• Develop, maintain and improve scalable data pipelines, data models, transformation workflows and calculation logic for the Scope 3 accounting framework.
• Support the migration of Scope 3 solutions from SAP BI Cubes to Databricks, translating business logic and data structures.
• Design and maintain analytical data warehouse and lakehouse solutions using dimensional modelling and medallion architecture.
• Simplify and automate data flows across multiple source systems, contributing to digitalization through AI and automation.
• Build automated validation, testing and reconciliation controls to ensure high data quality and auditable outputs.
• Investigate complex data issues, identify root causes and ensure the technical and logical consistency of calculation results.
• Support data governance through ownership, documentation, lineage, Unity Catalog and secure access controls.
• Contribute to CI/CD practices, including version control, automated testing, deployment and release management.
• Analyze complex data, support scenario modelling and develop dashboards and reporting solutions.

Required profile

• 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).
• Fluency in English; German and/or French are an advantage.
• Strong analytical, problem-solving and communication skills, curiosity and willingness to keep learning.

Required skills

• Proven experience with data platforms such as Databricks, Snowflake, Microsoft Fabric or Google BigQuery.
• Proven experience with Azure services including Data Factory, Storage Account and Key Vault.
• Coding in SQL, Python and PySpark.
• Code versioning and DevOps tools such as Azure DevOps or GitHub, and CI/CD practices.
• Familiarity with data governance concepts (data management, lineage, access controls, row-level security) is an advantage.
• Preferred: Data Engineering certifications, dbt experience.

Only direct applications will be considered. Salaries are competitive and aligned with local market benchmarks, depending on skills, education and training.