Senior Data Modeler

5+ years of experience

Ukraine

Remote

We are looking for a Senior Data Modeler for our client.
Founded in 2003, the company is a global technology consultancy specializing in digital transformation, data management, and AI-driven solutions. They focus on enhancing customer experiences and providing secure IT infrastructure. The company also offers expertise in Salesforce, UX/UI design, and loyalty programs, aiming to accelerate business value through integrated technology and industry insights.

Requirements:

5+ years of experience in data modeling and data warehouse design.
Expertise in Data Vault 2.0 and dimensional modeling.
Strong knowledge of data modeling tools such as SQLDBM, Erwin Data Modeler, Lucid, LucidChart, SQL Database Modeler, or Draw.io.
Hands-on experience with Azure and Databricks for data modeling and warehousing.
Proficiency in SQL for writing, optimizing, and troubleshooting complex queries.
Strong understanding of data warehouse architecture, ETL processes, and data integration strategies.
Experience in data governance, metadata management, and data cataloging.
Certifications in Data Modeling, Azure, or Databricks.
Strong analytical and problem-solving skills with an ability to work independently and within a team.
Upper-Intermediate English.

Preferred Qualifications:

Bachelor's degree in Engineering or a relevant field.
Experience with Oracle JDE is a plus.
Familiarity with big data processing, cloud-based data lakes, and advanced analytics.
Knowledge of data security, privacy regulations, and compliance standards.

Responsibilities:

Data Modeling: Design, develop, and optimize enterprise-level data models using Data Vault 2.0 and dimensional modeling approaches.
Data Warehouse Development: Lead and contribute to the architecture and design of data warehouses on Azure and Databricks.
Data Modeling Tools: Utilize industry-leading tools such as SQLDBM, Erwin Data Modeler, Lucid, LucidChart, SQL Database Modeler, or Draw.io for data modeling.
SQL Expertise: Develop and optimize complex SQL queries to support data modeling and warehousing requirements.
Data Governance & Quality: Ensure high data integrity, consistency, and governance across all data assets.
Collaboration: Work closely with data engineers, architects, and business stakeholders to translate business needs into logical and physical data models.
Performance Optimization: Optimize data models for query performance, storage efficiency, and scalability.
Documentation & Standards: Maintain proper data modeling documentation and ensure adherence to best practices and organizational standards.
Emerging Technologies: Stay updated with industry trends and new technologies in data architecture, modeling, and warehousing.
Design and implement Data Vault 2.0 models (Hubs, Links, and Satellites) to support enterprise-wide data integration and historical tracking.
Develop conceptual, logical, and physical data models that align with business needs and best practices.
Ensure data models are optimized for Databricks Lakehouse, Delta Lake, and Azure Synapse Analytics.
Define standards, best practices, and patterns for data modeling across various business domains.
Azure & Databricks Data Platform Integration
Work closely with data engineers to translate models into optimized physical structures within Azure Data Lake Storage (ADLS), Azure Synapse, and Databricks Delta Lake.
Utilize Unity Catalog and Data Governance frameworks for metadata and security management.
Implement data versioning, lineage tracking, and auditing mechanisms.
Ensure seamless integration with ETL/ELT pipelines using Azure Data Factory, Databricks Notebooks, and Delta Live Tables.