Data Modeller

Job Description

We are looking for an experienced, hands-on Data Modeler to design, develop, and maintain scalable data models that support enterprise data, analytics, and reporting needs.

The Data Modeler will work across data warehouses, data marts, and BI environments, with a focus on Snowflake and AWS. This role will collaborate with data engineering, analytics, BI, and business teams to translate business and technical requirements into logical and physical data models that enable reliable, consistent, and efficient data consumption.

What You Will Do

• Design, develop, and maintain conceptual, logical, and physical data models to support data warehouse, data mart, analytics, and reporting solutions.
• Develop and optimize dimensional and relational data models within Snowflake.
• Translate business and technical requirements into clearly defined data entities, attributes, relationships, and structures.
• Apply data warehouse and dimensional modeling principles to support reporting, analytics, semantic layers, and downstream data consumption.
• Collaborate with data engineers, BI developers, analysts, and business stakeholders to understand data requirements and develop scalable data models.
• Partner with data engineering teams to ensure data models align with ETL/ELT processes, source data structures, and data integration requirements.
• Review existing data models and recommend improvements to data quality, consistency, performance, scalability, and maintainability.
• Define and apply data modeling standards, naming conventions, and reusable modeling patterns across data solutions.
• Support metadata management, data lineage, data governance, and data quality initiatives.
• Create and maintain documentation for data models, entities, relationships, metadata, and data definitions.
• Participate in data model reviews and contribute to data architecture and modeling best practices.
• Support data solutions across Snowflake and AWS environments.
• Troubleshoot data-related issues and collaborate with technical teams to identify root causes and appropriate solutions.
• Participate in SDLC and Agile development activities and use JIRA to support work tracking and delivery.

What You Will Bring

• 3+ years of experience in data modeling, data warehousing, data engineering, or a related data field.
• Bachelors degree in Computer Science or a related field such as Information Systems, Mathematics, or Software Engineering.
• Hands-on experience designing conceptual, logical, and physical data models.
• Strong understanding of dimensional modeling, relational database design, and entity-relationship (ER) modeling.
• Hands-on experience with Snowflake.
• Strong proficiency in SQL and relational database concepts.
• Experience with data modeling tools such as ERwin, ER/Studio, or similar platforms.
• Experience working with data warehouses, data marts, semantic layers, and data consumption patterns.
• Experience with or knowledge of AWS cloud platforms and associated services.
• Knowledge of ETL/ELT methodologies and data integration concepts.
• Understanding of metadata management, data lineage, data governance, and data quality concepts.
• Understanding of data modeling standards, naming conventions, data definitions, and documentation practices.
• Experience working within SDLC and Agile methodologies.
• Experience using JIRA in an Agile development environment.
• Strong analytical and problem-solving skills with the ability to troubleshoot data-related issues.
• Strong written and verbal communication skills with the ability to collaborate effectively with technical and business stakeholders.

What Will Set You Apart

• Experience in the financial services industry or another highly regulated industry.
• Experience with DBT and modern data transformation practices.
• Experience with Airflow or other workflow orchestration technologies.
• Experience with Python for data processing or automation.
• Experience with Big Data technologies such as Hadoop or Spark.
• Experience supporting production-grade data platforms.
• Experience developing or supporting semantic data models for BI and analytics applications.
• Experience implementing metadata management, data lineage, data governance, or data quality frameworks.
• Experience establishing or contributing to enterprise data modeling standards, naming conventions, and reusable modeling patterns.