Data Analytics Engineer (m/w/d)
- Visualizing requirements: Based on customer requirements, you will create and maintain analytical data models and dashboards to ensure they meet the latest business needs.
- Ensuring data integrity and quality: To ensure high-performance use of reports and dashboards, you will create modular data models that simultaneously ensure data integrity and quality.
- DevOps is practiced throughout: As part of a DevOps team, you will independently develop data sources and data pipelines to ensure effective data provision for use cases and their implementation.
- Communication is key: You’ll be in constant, close contact with
your clients to ensure professional expectation management and client satisfaction,
your project team to ensure project success, and, of course,
the Woodmark team to foster knowledge sharing and mutual support.
Expertise is a given: You are comfortable with
- using data analysis tools such as Tableau, AWS QuickSight, KNIME, AWS Glue
- implementing analytical data models, e.g., in Data Vault 2.0 using native SQL, dbt Core, or Python
- applying data protection and security policies and adhering to best practices in this area
- working with different data structures (relational, JSON, XML) and their storage formats in layered models (3NF, Data Vault, Star Schema) and possesses an advanced understanding of
- working with various data sources and types, including unstructured data
Support the Making-of-a-Star: You enjoy using your experience to support other Woodmarkers, because we love diversity and you make a difference.
Fluent in English: You’re comfortable with the English language and English documentation, and you can follow along when English is spoken during project work.