Data Warehouse Modelling Engineer (Data Vault 2.0 + dbt)

Employment: Full-Time Minimum experience: Experienced Altenar is an international IT company founded in 2011, with offices in Malta, Greece, Georgia, the Isle of Man, and Uruguay. We specialize in high-load software development and provide one of the best technology solutions for the iGaming industry worldwide. About the Role We are looking for an experienced Data Warehouse Modelling Engineer to design, build, and maintain enterprise-grade data models using Data Vault 2.0 methodology within a modern ELT framework powered by dbt . Key Responsibilities: Design and implement Data Vault 2.0 models (Raw Vault and Business Vault) including Hubs , Links , Satellites , Point-in-Time (PIT) tables, and Bridges . Develop and maintain robust dbt projects for Data Vault implementation, leveraging macros, packages (e.g., datavault4dbt , AutomateDV / dbtvault), YAML configurations, and Jinja templating. Build staging layers, raw vault loading patterns, and business vault transformations following Data Vault 2.0 standards and best practices. Ensure high data quality, auditability, traceability, and historical tracking through proper hash key design, loading patterns, and effective dating. Collaborate with data architects, data engineers, and business stakeholders to translate business requirements into scalable Data Vault models. Optimize data models for performance. Implement dbt best practices: tests (unit + schema), documentation, selectors, CI/CD pipelines, and version control (Git). Support incremental loading strategies, handling of late-arriving data, and multi-source integration challenges. Contribute to the evolution of the data modelling framework and automation standards. Requirements Must-Have Experience: Strong hands-on experience (5+ years) in Data Vault 2.0 modelling on large-scale enterprise projects. Extensive expertise in building and maintaining Data Vault implementations using dbt (dbt Core or dbt Cloud). Deep understanding of Data Vault 2.0 components: Hubs, Links, Satellites (effectivity, multi-active, computed), PIT tables, Bridges, and Reference tables. Solid SQL skills and experience with modern data warehouses (Trino preferred, ClickHouse a plus). Technical Skills: Advanced proficiency in dbt — models, macros, tests, documentation, exposures, and project structuring. Experience with Data Vault automation packages ( datavault4dbt , AutomateDV , or similar). Strong knowledge of ELT/ETL patterns, data integration from multiple sources, and handling of changing business keys. Git, CI/CD for data (e.g., dbt Cloud jobs, GitHub Actions), and Infrastructure as Code. Familiarity with dimensional modelling (Kimball Star Schema) as a downstream consumption layer is a plus. Soft Skills & Qualifications: Excellent analytical and problem-solving skills with a strong focus on scalability and maintainability. Ability to work in agile environments and deliver incrementally. Strong communication skills — able to explain complex modelling concepts to both technical and non-technical stakeholders. Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field (or equivalent experience). Nice-to-Have: Certification in Data Vault 2.0 (from Data Vault Alliance or similar). Experience with dbt Cloud features (CI, Jobs, Discovery, etc.). Knowledge of data mesh, lakehouse architectures, or real-time Data Vault patterns. Python scripting for custom dbt macros or utilities. What we offer: Stable and flexible working environment Career growth opportunity Training and professional development events Health insurance for employees and close family members Teamwork and accountability Sense of community and defined company culture International work environment Diverse workplace Gym reimbursement after successfully passing probationary period