Application as Data Engineer

Data Engineer is a profession in IT / Data and Analytics, typically entered via BSc Computer Science FH. Anyone applying here should know these requirements and pitfalls - specific to the Swiss job market, not generic.

Technical Requirements

• Advanced SQL and data modelling
• Python for data pipelines
• Orchestration with Airflow, dbt or Azure Data Factory
• Cloud data platforms such as Databricks, Snowflake or Microsoft Fabric
• Data-protection-compliant processing of personal data

Personal Requirements

• Diligence - faulty pipelines often only surface weeks later
• Collaboration with business departments that don't fully know their own data
• Willingness to document data lineage

Common Mistakes in the Application

• Data volumes and processing frequency are missing - without them, 'pipeline' is meaningless
• No statement on data quality, even though it makes up most of the actual work
• The cloud platform is named, but not the role within it
• Regulatory requirements are left out, even though pharma and finance dominate this field

Typical Employers in Switzerland

Swisscom, SIX, UBS, Roche, Novartis, Swiss Post, Migros, Zurich Insurance.

Excerpt from a Cover Letter

Dear Ms. Amrein In my current role, I am responsible for the data pipelines behind an insurer's reporting: eleven source systems, around four million records daily, orchestrated via Azure Data Factory and dbt. Most of my work is not about building new pipelines, but about securing data quality at the handover points - we introduced validation rules that stop faulty loads before they reach a report.

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