Responsibilities & Qualifications
Develop & Scale Pipelines: You design and implement robust ETL/ELT pipelines to process large, complex volumes of data (Big Data) using both code-based and visual tools.
Semantic Data Modeling: You translate complex business processes into logical data models and help build a centralized, cross-departmental enterprise data model.
Data Quality & Lineage: You implement automated quality checks and monitor data flows from source to end product to guarantee seamless data lineage.
Code & Transformation: You write clean, high-performance code in PySpark and SQL to clean, aggregate, and prepare data for downstream analysis.
Cross-Functional Collaboration: You work closely with Data Scientists, Business Analysts, and business departments to quickly translate their requirements into production-ready data structures.
Initial practical experience in Data Engineering (as a Junior, e.g., through relevant internships/working student roles; as a Mid-Level, approx. 1–3 years of professional experience).
Solid knowledge of Python (especially in a Big Data context with PySpark) as well as proficiency in writing complex SQL queries.
Good understanding of modern data architectures (Data Lakehouse, distributed systems) and ideally experience with integrated all-in-one data platforms.
Familiar with relational and non-relational databases. You enjoy bringing order to unstructured mountains of data.
Analytical mindset, work in a structured manner, and possess a strong willingness to learn, allowing you to quickly adapt to new, complex software ecosystems.
Duration : permanent contract
Language : fluent in English, German is a plus
Start date : September
Location : Zurich - CH
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Develop & Scale Pipelines: You design and implement robust ETL/ELT pipelines to process large, complex volumes of data (Big Data) using both code-based and visual tools.
Semantic Data Modeling: You translate complex business processes into logical data models and help build a centralized, cross-departmental enterprise data model.
Data Quality & Lineage: You implement automated quality checks and monitor data flows from source to end product to guarantee seamless data lineage.
Code & Transformation: You write clean, high-performance code in PySpark and SQL to clean, aggregate, and prepare data for downstream analysis.
Cross-Functional Collaboration: You work closely with Data Scientists, Business Analysts, and business departments to quickly translate their requirements into production-ready data structures.
Initial practical experience in Data Engineering (as a Junior, e.g., through relevant internships/working student roles; as a Mid-Level, approx. 1–3 years of professional experience).
Solid knowledge of Python (especially in a Big Data context with PySpark) as well as proficiency in writing complex SQL queries.
Good understanding of modern data architectures (Data Lakehouse, distributed systems) and ideally experience with integrated all-in-one data platforms.
Familiar with relational and non-relational databases. You enjoy bringing order to unstructured mountains of data.
Analytical mindset, work in a structured manner, and possess a strong willingness to learn, allowing you to quickly adapt to new, complex software ecosystems.
Duration : permanent contract
Language : fluent in English, German is a plus
Start date : September
Location : Zurich - CH
#J-18808-Ljbffr
Data Engineer Arbeitgeber: SII Group Belgium
Als Teil der international agierenden SII Group bieten wir als Arbeitgeber ein dynamisches und unterstützendes Arbeitsumfeld, das auf Eigenverantwortung und kontinuierlicher Weiterentwicklung basiert. Unsere Mitarbeiter profitieren von flexiblen Arbeitszeiten, einem modernen Setup mit cloudbasierten Tools und einer Kultur, die offene Kommunikation und Vertrauen fördert. Zudem unterstützen wir individuelle Entwicklungsmöglichkeiten und bieten attraktive finanzielle Extras, um eine ausgewogene Work-Life-Balance zu gewährleisten.
