Job Description Template: Data Engineer
Use this template to write a data engineer job description for your Swiss SME. It covers the core role (data pipeline design, ETL processes, infrastructure), must-have technical skills and experience, nice-to-haves like cloud certification or ML familiarity, and what to include in your offer section (Pensum, location by canton, salary range in CHF, benefits, and language requirements).
A data engineer builds and maintains the systems that collect, store, and move data reliably across your organisation. They design pipelines, ensure data quality, and help analysts and stakeholders access what they need.
This template is designed for Swiss employers. Adapt the Pensum percentage, canton/city, salary band, and language requirements to match your role. Most Swiss job ads state the location at canton level (e.g. 'Zurich', 'Vaud', 'Basel-Landschaft').
What the role does
The data engineer designs and operates data pipelines that feed analytics, reporting, and machine-learning systems. They work with databases, cloud platforms, and scripting languages to move data reliably from source to destination.
This role sits between data producers (applications, sensors, APIs) and data consumers (analysts, data scientists, business intelligence teams). It is technical, hands-on, and involves on-call or incident response depending on your setup.
- Design, build, and maintain ETL (extract, transform, load) or ELT pipelines
- Manage data warehouses, data lakes, or lake-house architectures (Snowflake, BigQuery, Databricks, etc.)
- Monitor data quality, latency, and pipeline performance; troubleshoot failures
- Document data lineage, schemas, and transformation logic for other teams
- Collaborate with analysts, engineers, and business stakeholders on data requirements
- Optimise queries and infrastructure for cost and performance
Must-have requirements
Look for candidates with proven experience building data pipelines in production, either in a dedicated data role or as part of backend or analytics engineering work. Technical depth matters more than years of experience.
They should be comfortable with SQL, at least one programming language (Python, Java, Scala, Go), and version control (Git). Experience with a cloud platform (AWS, GCP, Azure) or on-premise data infrastructure is essential.
- 3–5 years building or maintaining data pipelines, ETL tools, or data warehouses
- Strong SQL: writing and optimising queries, understanding schemas and indexes
- Proficiency in Python, Java, Scala, or similar; ability to write clean, testable code
- Hands-on experience with at least one cloud platform (AWS, GCP, Azure) or Hadoop/Spark
- Understanding of relational and non-relational databases; familiarity with at least one
- Ability to work in German or French (your team's working language); English is nearly always an asset
Nice-to-have requirements & what to offer
Candidates with cloud certifications (AWS Solutions Architect, GCP Professional Data Engineer), exposure to real-time streaming (Kafka, Pub/Sub), or experience with dbt, Airflow, or similar orchestration tools often stand out. Familiarity with machine-learning pipelines or data governance frameworks is a bonus.
Offer a Pensum (percentage of full-time, e.g. 80–100%), named location by canton (e.g. 'Zurich' or 'Lucerne'), and a salary range in CHF (typically 120,000–180,000 gross per annum for a mid-level data engineer in major Swiss cities, less in smaller regions). Include 13. Monatslohn, pension contributions (BVG), and flexible working if available. State the working language clearly.
- Cloud certifications (AWS, GCP, Azure Data Engineer) or Databricks accreditation
- Experience with real-time or streaming data (Kafka, Google Pub/Sub, Kinesis)
- Familiarity with data orchestration tools (Airflow, dbt, Prefect) and modern DevOps practices
- Background in machine-learning or analytics engineering; interest in data governance
- Pensum: 80–100% (specify your flexibility). Location: name your canton and/or city.
- Salary: quote a realistic range in CHF; include 13. Monatslohn, BVG, and any perks (home office, courses, equipment budget)
Frequently asked questions
- Should I include a language requirement in my data engineer job ad?
- Yes. State the working language upfront (e.g. 'German and English', 'French', 'English and Italian'). Most Swiss data roles require German or French because your team communicates in one of these languages. English is often a secondary requirement for international collaboration or documentation.
- What Pensum should I advertise for a data engineer?
- Most data engineers in Switzerland work 100% (full-time). Some larger companies offer 80% for experienced candidates or those seeking flexibility. Be clear: 80–100% means you are open to negotiation; 100% means full-time only. State it as a percentage, not hours per week.
- How much should I offer in salary for a data engineer in Switzerland?
- Mid-level data engineers typically earn 120,000–180,000 CHF gross per annum in Zurich, Geneva, and Basel; 100,000–150,000 CHF in smaller cities. Junior (1–2 years): 90,000–120,000 CHF. Senior (5+ years): 150,000–220,000 CHF. Always include the 13. Monatslohn (13th month bonus, legally standard in most Swiss GAVs), BVG pension, and any other benefits in your total offer.
General information for Swiss employers, not legal advice. Have a lawyer confirm anything with legal consequences.