Month 1-2:

• Get familiar with Sika’s data architecture, technology stack, and main data sources (e.g., SAP S/4Hana, Salesforce, SAP ByDesign).
• Shadow team members to understand daily workflows and best practices in data engineering.
• Support the team with basic data extraction, data entry, and documentation tasks.
• Get certified in different technologies such as Azure, Databricks and dbt.

Month 3-4:

• Learn to use key data engineering tools such as Azure Databricks, dbt, and Azure Data Factory through guided tutorials and hands-on exercises.
• Assist in maintaining and updating simple ETL/ELT pipelines under supervision.
• Help monitor data quality and perform basic data validation checks.

Month 5-onwards:

• Support teammates in preparing data for analytics and reporting use cases.
• Help create and update documentation, templates, and user guides for data processes.
• Participate in troubleshooting sessions and learn how to resolve common data pipeline issues.
• Continue to build your skills by attending internal workshops and collaborating on small-scale data projects with guidance from mentors.

• Recently completed a degree in Data Science, Computer Science, Management of Information Systems, or a related field; Relevant certifications on Data Engineering are a plus.
• Strong interest in data engineering and analytics; relevant coursework or project experience is a plus.
• Familiarity with programming languages such as SQL and Python; knowledge of PySpark or dbt is an advantage.
• Interest in cloud platforms and services (e.g., Azure Databricks, Azure Data Factory); prior experience is a plus but not required.
• Familiarity with code versioning tools such as Azure DevOps or GitHub is a plus.
• Eager to learn about domain-oriented data management approaches, such as Data Mesh.
• Strong analytical and problem-solving skills.
• Fluency in English; proficiency in additional languages is a plus.