Data Modeller
- 3+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols). Experience on MongoDB would be an advantage
- Good knowledge of metadata management, data modelling, and related tools (Erwin or Visual Paradigm or others) required
- Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre contexts is desired
- Experience in team management, communication, and presentation
- Strong communication skill, good oral English
For our Client we are looking for an experienced Data Modeller.
📍 Location: Kraków, hybrid work model – 2 days per week in the office, 3 days remote
🕒 Cooperation model: [Full-time / B2B]
📍 Project for our Client from the financial sector
The team
The team's organisation consists of individuals working both on global, regional, and local projects in support of all Global Businesses and Global Functions. The individual(s) in the role of Data Modelling will be responsible for modelling data within specific Businesses, Functions and/or Geographies and will work with the Data CIOs and Data Officers and their respective teams as needed.
The Role
The data modeler designs, implements, and documents data architectures and data models for solutions, which include the use of application, relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, operations, machine learning, data science, and other business interests.
The successful candidate will:
- Be responsible for the development of the conceptual, logical, and physical data models, oversight of the implementation of RDBMS, operational data stores (ODS), application databases, data marts, and data lakes on target platforms (SQL/NoSQL/cloud/on-prem)
- Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively