Public summary
A company specializing in AI-native systems is seeking a Senior Data Modeler to design and deliver scalable data models using Data Vault 2.0 techniques. The role involves working with clients to create business-aligned, reusable data assets supporting enterprise data strategies. Key responsibilities include maintaining modeling consistency, collaborating with cross-functional teams, and mentoring peers. Candidates should have 4+ years in enterprise-scale data modeling, strong SQL skills, and experience in agile and DevOps environments. Fluency in English and willingness to travel to client sites are required.
Location and work setup
- Location
- Berlin
- Remote status
- Hybrid
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Translate complex business requirements into robust data models including conceptual, logical, and physical layers focused on Data Vault 2.0. Design and implement scalable, auditable data products using Data Vault patterns. Ensure modeling consistency and alignment with enterprise standards across data domains and teams. Collaborate with stakeholders and data teams to clarify requirements, define model scope, and manage delivery timelines. Integrate models with modern data platforms using CI/CD, Git, and automation tools. Act as a subject matter expert in modeling approaches, mentoring peers and guiding teams on advanced Data Vault use cases.
Qualifications
At least 4 years of experience in data modeling with proven delivery of enterprise-scale data solutions. Proficient in Data Vault and dimensional modeling techniques with a solid understanding of conceptual, logical, and physical data models in modern ecosystems. Knowledge of data governance, metadata management, and business term alignment. Experienced in Agile environments using DevOps toolchains including CI/CD and Git. Strong communication and collaboration skills to work with client teams. Fluent English is required; German is not mandatory. Additional desirable qualifications include Data Vault 2.0 certification, and experience with dbt, Databricks, and CI/CD workflows for data models.