Senior Data Modeler Consultant
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Key skills for this role
About the Role
Devoteam seeks a Senior Data Modeler Consultant to design and optimize enterprise data architecture. The role involves conceptual, logical, and physical modeling for OLTP, OLAP, and Data Lakehouse environments, ensuring data is structured for performance and scalability.
Key Skills for This Role
Responsibilities
- Review current data models to understand the AS IS environment
- Plan, design and maintain blueprints of TO BE data models for OLTP, OLAP, and Enterprise Data Lakehouse environments
- Understand business processes and translate them into robust data requirements
- Design 3NF, Dimensional Models (Kimball/Star Schema), and Data Vault 2.0
- Transform unstructured data into structured data by fixing errors and eliminating redundancies
- Optimize query performance through indexing, partitioning, and materialization strategies
- Establish and enforce data governance best practices, naming standards, and metadata management
- Specify rules for data security and compliance, and classify data according to sensitivity
- Maintain data schemas using modern modeling tools and ensure documentation is accessible
Requirements
- B.Sc. degree with 5+ years of dedicated data modeling experience in enterprise relational databases and columnar databases
- SQL proficiency to write, read, and optimize complex transactional and analytical queries
- Experience modeling for cloud data warehouses/lakehouses (e.g., SQLSERVER, Hadoop, Snowflake, BigQuery, Databricks)
- Proficiency with ER/Studio, Erwin or similar data modeling software
- Understanding of semi structured data (JSON, Parquet) and NoSQL databases (MongoDB, Cassandra)
- Familiarity with ETL tools for defining data transformation rules
- Soft skills: Communication, presentation, business needs, ability to lead or mentor a team
Full Job Posting
Company Overview
- Devoteam is a technology consulting company with over 25 years of experience, present in 18+ countries across EMEA and beyond.
- Devoteam's culture is based on values: Respect, Frankness, Passion, and principles: Fair and courageous, Ambition and results, Learning and innovating, Caring and sharing.
Job Summary
- Design, implement, and optimize enterprise data architecture and models using relational, dimensional, and NoSQL databases.
- Ensure data is structured for high performance, clarity, and long term scalability across operational and analytical systems.
- Act as 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 TO BE data models for OLTP, OLAP, and Enterprise Data Lakehouse environments.
- Business Alignment: Understand business processes and translate them into robust data requirements.
- Multi Paradigm Modeling: Design 3NF, Dimensional Models (Kimball/Star Schema), and Data Vault 2.0.
- Data Quality: Transform unstructured data into structured data by fixing errors and eliminating redundancies.
- 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, and metadata management.
- Data Security: Specify rules and guidelines for ensuring data security and compliance.
- Tooling & Documentation: Maintain data schemas using modern modeling tools and ensure documentation is accessible.
Qualifications
- B.Sc. degree with a minimum of 5+ years of dedicated data modeling experience in enterprise relational databases and 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 creating ERDs.
- 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).
- Physical Data Management: Understand current data storage constraints and define TO BE needs with growth allocation.
- Data Integration: Familiar with ETL tools to define rules for data transformations.
- 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.
Additional Information
- Business Unit: DAIC
- Level: Mid senior level
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