Data Engineer CV: Example and Template
How to structure your CV as a Data Engineer in Switzerland - with measurable results from data pipelines, data warehouses and cloud platforms.
Currently 37 open Data Engineer positions in Switzerland, across 2 cantons, 8 of them from the last 7 days. Lombard Odier advertises the most.
CV example — two-page template
This template is editable straight away — or upload your existing CV and it is carried into this layout automatically.
Check your CV against real Swiss job adverts
The check compares your CV with what Swiss adverts actually ask for — structure, language level, missing evidence.
Check my CVWhat qualification do you need to work as a Data Engineer in Switzerland?
The Swiss market most commonly requires a BSc or MSc from a university of applied sciences or ETH/EPFL in computer science, data science or business informatics - but the path via an EFZ in IT with further education is equally recognised.
State your qualification using the correct Swiss terminology, for example 'BSc FH Computer Science, Data Engineering major' or 'MSc ETH in Data Science'. If you entered the field via a vocational apprenticeship, list 'IT Specialist EFZ, Application Development' and add CAS or DAS programmes below it, such as the CAS in Data Engineering from Lucerne University of Applied Sciences, the CAS in Machine Learning from FHNW, or a DAS in Data Science from ZHAW. Recruiters in Switzerland recognise these titles and read them as a signal of practical competence.
For foreign diplomas, it is worth noting their recognition: write the title in the original language, add the Swiss equivalent in brackets, and mention an assessment from Swiss ENIC if available. Equally important is your labour market status - a note such as 'C permit' or 'EU/EFTA citizen, B permit' in the header prevents follow-up questions and speeds up pre-selection.
Certificates don't replace a degree but carry significant weight in Data Engineering. Practically relevant ones include Microsoft Azure Data Engineer Associate (DP-203), Databricks Certified Data Engineer Associate or Professional, SnowPro Core, Google Professional Data Engineer and AWS Certified Data Engineer. List at most four of them, with the year, and leave out expired cloud certificates.
How should you present your professional experience as a Data Engineer?
For each position, describe the data platform, the volume, and the business impact of your pipelines - not the list of technologies used.
Give each position a short context sentence covering the industry, the size of the data landscape, and your role within the team. Follow this with three to four bullet points with numbers: number of pipelines or dbt models, data volume per day, reduction in load time, number of production incidents, number of data warehouse users, or cloud cost savings in CHF. Phrases like 'reduced daily closing load time from 6h40 to 52 minutes' are far more compelling than 'responsible for ETL processes'.
Make the maturity level of your work visible. Mention modelling approaches (Data Vault 2.0, Kimball star schema), orchestration, CI/CD, test coverage with dbt or Great Expectations, monitoring, and data contracts. This is exactly how Swiss hiring managers judge whether you can run a platform or have only written individual jobs. For banking and insurance projects, add governance aspects such as Unity Catalog, row-level security, revFADP, or FINMA outsourcing requirements.
A separate 'Technologies' block at the end groups your stack by category: languages (SQL, Python, Scala), processing (Spark, Kafka, Flink), platforms (Snowflake, Databricks, BigQuery), orchestration (Airflow, dbt, Dagster), and infrastructure (Terraform, Kubernetes, Azure DevOps). Only list what you can explain on a whiteboard in an interview - technical interviews in Switzerland usually include an SQL exercise and a modelling task.
How long should the CV be, and does it need a photo?
Two pages is the standard, and a professional photo remains common in Switzerland, though not mandatory.
Keep it to a maximum of two pages, even with ten years of experience: page one with your profile, at-a-glance summary, skills, and current position; page two with earlier experience, education, certificates, and languages. Summarise positions that go back more than twelve years in a single line. Submit the CV as a PDF and name the file following the pattern 'CV_Lastname_Data-Engineer.pdf'.
A professional headshot in the top right corner reflects Swiss convention and is expected by many HR departments. On the other hand, leave out marital status, religion, and details about family members. What's necessary is your place of residence with canton, a phone number in the format 079 000 00 00, a professional email address, your GitHub or GitLab profile, and your labour market status.
Add two Switzerland-specific details that recruiters look for directly: your availability date including notice period, and your desired workload percentage, e.g. 80-100%. Salary expectations don't belong in the CV - save them for the interview or the application form; as a guideline, Data Engineers in Switzerland earn roughly between CHF 95'000 and CHF 145'000 per year depending on experience and region. Finally, align your language and terminology with the job posting, since applications are often screened via an applicant tracking system.
Where Data Engineer are hired in Switzerland
How the 37 open positions are spread across the cantons.
Figures as a table
| Canton | postings |
|---|---|
| Zürich | 2 |
| Tessin | 1 |
Which languages the postings require
Of 14 postings that state a language — in brackets, those requiring professional level.
Figures as a table
| Language | postings |
|---|---|
| English | 11 (9) |
| German | 8 (4) |
| French | 1 (1) |
Who hires Data Engineer in Switzerland
Employers with the most open positions. Staffing agencies are excluded.
Figures as a table
| Employer | postings |
|---|---|
| Lombard Odier | 2 |
| b.telligent Romania | 2 |
| SII Group Switzerland | 2 |
| Logitech | 2 |
| YO IT Consulting | 2 |
| enshift AG | 1 |
Full-time or part-time?
How the positions are advertised.
Figures as a table
| Workload | postings |
|---|---|
| Vollzeit / plein temps | 28 |
| Temporär | 1 |
The CV in full
To read through and reuse.
Nadine Brunner
Data Engineer, MSc ETH Zurich in Data Science
Data Engineer with seven years of experience building batch and streaming pipelines for retail and insurance data in Switzerland. I am responsible for a lakehouse stack on Azure Databricks with dbt, Airflow and Snowflake, which processes around 4 TB daily and serves over 300 business users. My focus areas are data modelling according to Data Vault 2.0, cost optimisation of cloud workloads, and data governance requirements arising from the revFADP and FINMA circulars on outsourcing.
What sets me apart
Lakehouse architecture instead of a script collection: I build Medallion architectures (Bronze/Silver/Gold) with Delta Lake, Unity Catalog and dbt models including tests, lineage and versioning - not grown SQL jobs without documentation.
Data protection under the revFADP from day one: I implement pseudonymisation, row-level security and documented data flows by design, including data residency in Swiss Azure regions for FINMA-relevant workloads.
Cost-conscious cloud engineering: I measure costs per pipeline and query: cluster rightsizing, partition pruning and materialisation strategies reduced the monthly Snowflake bill by CHF 11'000.
Bridge between business and platform: I run requirements workshops with actuarial, controlling and marketing teams in German and French, translating KPI definitions into a shared semantic layer.
Key achievements
Data warehouse migration without downtime. Migrated 240 Oracle jobs to Snowflake and dbt in 11 months; reduced daily closing load time from 6h40 to 52 minutes, cutting operating costs by 28%.
Streaming platform for branch data. Built a Kafka and Structured Streaming pipeline for 190 branches; sales data is now available in 90 seconds instead of after 24h, improving replenishment planning by 12%.
Made data quality measurable. Introduced 640 Great Expectations and dbt tests plus SLA monitoring; reduced faulty reports per quarter from 34 to 3, with mean resolution time down to 45 minutes.
Experience
Lead Data Engineer — Helvetia Datawerk AG, Zurich, since 03/2021
Insurance group with 1'400 employees; responsible for the lakehouse platform and a team of 5 Data Engineers.
- Consolidated 180 pipelines on Azure Databricks and Airflow, reducing production incidents per month from 21 to 4
- Built a Data Vault 2.0 model for claims and policy data with 95 hubs and links, shortening time-to-market for new KPIs from 6 to 2 weeks
- Introduced Unity Catalog with role-based access for 320 users, fully closing internal audit findings
- Reduced cloud costs by CHF 11'000 per month through cluster policies, auto-termination and a partitioning strategy
Data Engineer — Alpretail Analytics GmbH, Bern, 08/2018 - 02/2021
Retail group with 190 branches; built the analytics platform from scratch.
- Implemented Kafka streaming for point-of-sale data from 190 branches, reducing latency from 24h to 90 seconds
- Built a Snowflake data warehouse with 45 dbt models, migrating 60 Power BI reports to a single source of truth
- Reduced nightly ETL runtime from 5h to 70 minutes by switching to incremental load logic
- Established CI/CD with Azure DevOps, increasing deployment frequency from monthly to 12 releases per month
Junior Data Engineer / BI Developer — Seetal Informatik AG, Lucerne, 09/2016 - 07/2018
IT service provider for SMEs; projects in SQL Server, SSIS and reporting.
- Developed and documented 24 SSIS packages for 7 client accounts, reducing the nightly run error rate by 65%
- Modelled a star schema for financial reporting with 14 dimensions, shortening month-end reporting from 3 days to 4 hours
- Introduced automated data reconciliation in Python, eliminating around 120 hours of manual work per quarter
Education
MSc ETH, Data Science — ETH Zurich · 2016
BSc FH, Computer Science, Data Engineering major — Lucerne University of Applied Sciences - Computer Science · 2014
Federal VET Diploma, IT Specialist EFZ, Application Development — Berufsfachschule Zug · 2010
Microsoft Certified: Azure Data Engineer Associate (DP-203) · Databricks Certified Data Engineer Professional · SnowPro Core Certification · dbt Analytics Engineering Certification
Common questions
- What language should I write my CV in as a Data Engineer?
- 57% of adverts are in English, 35% in German. In this occupation two versions earn their keep.
- What language level do Data Engineer adverts ask for?
- English in 79% of adverts that state a requirement, 82% of them at professional level. "Good knowledge" will not do — give A2 to C2.
- Are Data Engineer roles offered full or part time?
- 100% full time, only 0% part time. If you need part time, say so early rather than leaving it open.
- Who hires Data Engineer in Switzerland?
- Currently Lombard Odier, b.telligent Romania, SII Group Switzerland, among others. Their adverts are the best word list for your own CV.