Senior Data Engineer at Experis Schweiz

Berlin, Berlin, Germany -

Full Time

Start Date

Immediate

Expiry Date

23 Dec, 26

Salary

50000.0

Posted On

24 Sep, 26

Experience

4 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Information Technology & Services

Description

Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related technical field; or equivalent training and professional experience
5+ years of experience in ETL/ELT, data warehousing, Business Intelligence, and integrating data processing/workflow management tools into pipeline design
5+ years building and maintaining end-to-end data systems using Python, Scala, or similar programming languages
Solid experience in utilising SQL for data analysis, investigating data issues, diagnosing root causes, and designing effective solutions
Experience in working with cloud-based data technologies, preferably on Microsoft Azure, within continuous integration and delivery (CI/CD) environments
Demonstrated experience working with large-scale datasets using Databricks, PySpark, Spark Streaming, and Delta Lake
Hands-on experience with structured, semi-structured, and unstructured data across various storage systems, including relational databases (RDBMS), data warehouses, in-memory caches, and document databases
Familiarity with cloud storage solutions such as Azure Data Lake and Blob Storage
Solid understanding of data modelling principles (experience with Data Vault is a plus) and strong skills in system design, implementation, and testing
Experience with event-driven architectures (e.g., Kafka, Event Hubs, Apache Flink) and containerised microservices platforms (e.g., Kubernetes, Docker, Helm Charts)
Knowledge and practical use of dbt (data build tool), experience with BI tools
Excellent communication and collaboration skills, ability to provide technical leadership to other developers

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Responsibilities

Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related technical field; or equivalent training and professional experience
5+ years of experience in ETL/ELT, data warehousing, Business Intelligence, and integrating data processing/workflow management tools into pipeline design
5+ years building and maintaining end-to-end data systems using Python, Scala, or similar programming languages
Solid experience in utilising SQL for data analysis, investigating data issues, diagnosing root causes, and designing effective solutions
Experience in working with cloud-based data technologies, preferably on Microsoft Azure, within continuous integration and delivery (CI/CD) environments
Demonstrated experience working with large-scale datasets using Databricks, PySpark, Spark Streaming, and Delta Lake
Hands-on experience with structured, semi-structured, and unstructured data across various storage systems, including relational databases (RDBMS), data warehouses, in-memory caches, and document databases
Familiarity with cloud storage solutions such as Azure Data Lake and Blob Storage
Solid understanding of data modelling principles (experience with Data Vault is a plus) and strong skills in system design, implementation, and testing
Experience with event-driven architectures (e.g., Kafka, Event Hubs, Apache Flink) and containerised microservices platforms (e.g., Kubernetes, Docker, Helm Charts)
Knowledge and practical use of dbt (data build tool), experience with BI tools
Excellent communication and collaboration skills, ability to provide technical leadership to other developers