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.
Start date : September
Location : Zurich - CH
Duration : permanent contract
Language : fluent in English, German is a plus
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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.
Start date : September
Location : Zurich - CH
Duration : permanent contract
Language : fluent in English, German is a plus
#J-18808-Ljbffr
