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Tech for People Unlocks the Future

At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us.
With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.

Devoteam Culture & Values:
True innovation is born from a powerful culture, fused with meaningful values.

Culture:

Fair and courageous
Everyone is treated fairly – this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.

Ambition and results
Ambition is nurtured at every step – this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.

Learning and innovating
Curiosity and learning are at our core – this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.

Caring and sharing
A caring attitude is infused into our culture – this encourages sharing. We believe in the power of teams, we promote support and collaboration.
At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers, 

Values:

1. Respect
2. Frankness
3. Passion

Knowing that success is the result of collaboration. Alone, we go faster, but together, we go further.

To know more about us, please visit: www.devoteam.com
 

Summary Introduction:

Design, implement, optimize enterprise data architecture and models that represent complex data using relational, dimensional, and NoSQL databases, and ensure data is structured for high performance, clarity, and long-term scalability across both operational and analytical systems. Data Modeler will be the translator between business stakeholders and data engineering teams.

Key Responsibilities: 

• Assessment - Review current data models to understand the AS-IS environment.
• Conceptual, Logical, and Physical Modeling - Plan, design and maintain blueprints of the TO-BE data models for OLTP (operational), OLAP (analytical), and Enterprise Data Lakehouse environments and how data will be stored, managed and used.
• Business Alignment - Understand business processes and translate them into robust data requirements and review current report design documents to understand where data model structures can address business requirements.
• Multi-Paradigm Modeling - Designing 3NF (Third Normal Form) for transactional databases, Dimensional Models (Kimball/Star Schema) for data warehousing, and Data Vault 2.0 for scalable enterprise data lakes.
• Data Quality - Transform unstructured data into structured data by fixing errors, eliminate redundancies and unnecessary data to optimize data systems.
• Performance Optimization - Optimize query performance through smart indexing, partitioning, and materialization strategies.
• Data Governance - Establish, enforce and implement best practices, data naming standards, data definitions, maintain data maps and relevant diagrams for data systems and metadata management.
• Data Security - Specify rules and guidelines for ensuring data security and compliance. Define procedures for ensuring data are classified according to their sensitivity.
• Tooling & Documentation - Maintain data schemas using modern standards modeling tools and ensure documentation is accessible to both technical and non-technical users.

• B.Sc. Degree with a minimum of 5+ years of dedicated data modeling experience in enterprise relational databases, columnar databases.
• SQL Proficiency - Write, read, and optimize complex SQL transactional and analytical queries
• Modern Data Stack Familiarity - Experience modeling for cloud data warehouses/lakehouses (e.g., SQLSERVER, Hadoop, Snowflake, BigQuery, Databricks), working alongside transformation tools (e.g., dbt), and create ERDs for relational systems and dimensional diagrams.
• Tooling - Proficiency with ER/Studio, Erwin or similar data modeling software.
• NoSQL/Unstructured Data - Understanding of when and how to model semi-structured data (JSON, Parquet) and NoSQL databases (MongoDB, Cassandra) alongside relational data.
• Physical Data Management - Understand current data storage constrains and define TO-BE needs with growth allocation.
• Data Integration - Familiar with ETL tools to define the rules for data transformations and prepare data for big data analytics.
• Soft Skills: Communication, presentation skills, Business needs, able to lead or mentor a team. 

Certificates: W3school SQL Certification, DAMA-CDMP Certification, Microsoft: Azure Data Engineer Associate. 

Business Unit: DAIC

Level: Mid-senior level