Are you looking for the next challenge in your career?
Would you like to be part of an exciting highly qualified team of professionals in an international environment?
We are currently looking for a qualified Data architect & Data Modeler (LS Sector). International Project
Join an international division and work alongside with some of the most talented engineers and technicians from all over the world.
Your benefits:
- Competitive Salary.
- Long-term secure contract.
- International Project with top technologies
- Possibility of working remotely with a flexible schedule.
- Integration in a highly qualified team of professionals.
- Travel abroad with your project.
- Specialized training and continuous professional development.
- Social benefits and flexible compensation plan.
Responsibilities
1. Landscape & Ecosystem Analysis
- Conduct discovery across operational, analytical, and R&D teams to map current data stores, data inputs and outputs, software APIs, and data silos.
- Perform toolchain and data standard assessments, identifying gaps in vendor interoperability, semantic consistency, and data lineage.
- Define strategy for legacy repositories: decide which systems stay, migrate, or convert to standardized data layers (e.g., converting vendor-proprietary formats to Allotrope-compliant standard structures).
2. Standardization & Ontologies (e.g. via Allotrope Framework)
- Operationalize semantic standards.
- Establish data models utilizing Allotrope Simple Models (ASM) / Allotrope Data Models (ADM) and Allotrope Data Format (ADF) to standardize analytical data captured across disparate instruments (e.g., LC/MS, HPLC, Plate Readers).
- Build unified controlled vocabularies, master metadata registries, and semantic mappings between vendor-native telemetry and enterprise-standard taxonomy.
3. Connected Platform Architecture & Snowflake Modeling
- Design a hybrid/multi-domain data platform architecture that bridges core enterprise platforms with domain-specific repositories.
- Model domain entities into Data Products (Experiment, Sample, Instrument, Instrument Raw Data).
- Establish cross-domain entities linkage.
4. Governance & End-to-End Enablement
- Define consuming personas and define data governance approach.
- Enable Data Scientists and Engineers by serving semantic layers, feature stores, and queryable APIs that preserve contextual lineage and metadata.
- Own end-to-end delivery: from semantic architecture diagrams and dbt models to production deployment, tool integration, and team training.
Key Requirements & Qualifications
- Experience: 8+ years in Data Architecture & Modeling, with proven leadership in scientific, biotech, pharmaceutical, or advanced R&D digital transformation.
- Ontologies & Standards: hands-on experience with the Allotrope Framework (AFO, ASM, ADM, ADF), FAIR data principles.
- Snowflake and AWS Expertise
- Data Product & Domain Modeling: Strong proficiency in Data Mesh, Dimensional Modeling (Kimball), Data Vault 2.0, and modeling core entities (Sample, Experiment, Instrument Data)
- Data Lead, Data Architecture, Data Modeling, Data Engineering, Databricks, Snowflake, Azure, AWS o Life Sciences
We positively value all work or study experience abroad.
All positions require a high level of English (at least B2) - please send your detailed CV in English.