Data Engineer (80-100%)

Zurich, CH

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Veröffentlicht:27 Januar 2026
Pensum:80 – 100%
Arbeitsort:Zurich, CH

SIX drives the transformation of financial markets.

What sets us apart drives us ahead: between local roots and global relevance, we are a unique blend of tradition and future, of foundation and growth. We value bright minds and inspire them to grow with their ideas. Come and shape the future of finance with us.

Data Engineer (80-100%)

Zurich |working from home up to 40% | Reference 7594

Do you want to shape the future of Swiss payments with data? Are you passionate about building scalable data solutions and applying modern analytics and AI in a highly dynamic environment?

Then our Data Science team within Banking Services at SIX wants to hear from you!

Banking Services plays a central role in orchestrating Swiss payments, providing critical infrastructure for interbank payments as well as card-based and mobile transactions. Embedded in this business unit, our Data Science team enables data-driven decision-making and innovation for both internal stakeholders and external customers.

In this role, you will collaborate closely with business representatives, engineers, and analysts to unlock the value of data and deliver impactful, production-ready solutions.

What You Will Do

design, implement, and optimize scalable and fault-tolerant Python-based ETL pipelines in a cloud environment (Databricks, Azure Data Factory)

build robust data ingestion pipelines from databases and files (e.g. CSV, Parquet), including schema mapping, data quality checks, and error handling

deliver clean, validated, and well-structured datasets to downstream applications such as invoicing and operational systems

develop and maintain access-controlled Power BI dashboards and support their integration into an external-facing portal

continuously learn and apply modern data engineering concepts

What You Bring

4+ years of professional experience in Data / Machine Learning / Software Engineering, or related roles

a bachelor’s or master’s degree in Computer Science, a quantitative field, or an equivalent qualification

strong proficiency in production-ready Python and SQL, with solid engineering practices (testing, code reviews, documentation)

proven experience building and operating data services, APIs, and data stores in production environments with hands-on experience in Azure services (Databricks, ADF, Power BI) considered a plus