About this role
About us
As Switzerland’s leading digital hub, we provide our media and platforms with ideal framework conditions, support them through investments in technology, and create space for them to develop individually. We stand for interdisciplinary collaboration, innovation, and dynamic development.
We are on the move – and want to keep moving. We are farsighted. We are proactive. We are courageous. We are TX. TX Services is a part of TX Group.
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About the job
You will be joining the Data & AI Foundation Team within the AI & Data department at Tamedia. We are a team of data engineers and tech experts who work together to turn raw data into reliable, actionable insights that power editorial, product, and marketing decisions across Tamedia's portfolio of brands.
We operate in a dynamic, cross-functional environment, collaborating closely with data scientists, product managers, and business stakeholders across multiple locations. We value technical rigor, intellectual curiosity, and a pragmatic mindset.
This is a temporary position for 6 months (maternity leave cover ), with the possibility of extension. As a Data Engineer , you will support the team primarily by maintaining and expanding our AWS data lakehouse infrastructure, building reliable pipelines, and delivering clean analytical data models.
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What would you do?
- Design, build, and maintain robust ETL/ELT pipelines for the centralized data lakehouse using DBT and Argo Workflow, ensuring data is reliable, well-tested, and documented
- Support and optimize our AWS data lakehouse infrastructure (S3, Athena, Glue), ensuring high data quality and modern operational standards
- Develop and optimize analytical data models within the lakehouse that serve as the foundation for dashboards and analytics use cases across the company
- Ensure data quality, integrity, and performance across the data lakehouse platform
- Collaborate closely with data analysts and scientists to understand their needs and translate them into robust data structures and pipeline models
Critically assess incoming data requirements, challenge assumptions, identify meaningful metrics, and help stakeholders define what they need to measure
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What should you bring?
Must-have
- 2+ years of experience in a data engineering or similar data-focused development role
- Solid, hands-on experience with DBT (models, tests, documentation, incremental strategies)
- Experience with AWS S3 and the broader AWS data lakehouse ecosystem (Athena, Glue, or similar)
- Proficiency in Python for data processing and pipeline development
- Solid command of SQL, including complex transformations and query optimization
- Good analytical thinking, ability to question requirements, understand business context, and translate business requirements into technical solutions
- Strong data intuition: capable of independently assessing data models/metrics and proactively flagging issues
- Fluency in English
Nice to have
- Experience with workflow orchestration tools (e.g. Argo Workflow, Airflow, Matillion)
- Familiarity with data quality frameworks and testing practices
- Experience working in a media, publishing, or digital platform environment
- Higher education degree in a relevant field (computer science, statistics, engineering, or equivalent)
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Our hiring process
Our hiring process consists of 4 steps:
- HR call
- Team lead call: deep-dive into your data engineering experience and approach to problem-solving
- Technical case: a practical exercise reflecting the kind of work you'd do on the team
- Meet the team: get to know your future colleagues and ask any remaining questions
During the HR Call, we will cover everything that might be interesting for you, but also details on benefits, plans, and administrative things.
You can learn more about our perks on our website.
A 3D office tour is available here .