BI Data Modeler Engineer

Responsibilities: Create and maintain conceptual, logical, and physical data models that support reporting and analytics across enterprise systems. Collaborate with stakeholders to translate business needs into scalable data structures and solutions. Contribute to the design of Extract, Transform, Load (ETL) processes to ensure efficient data movement into Business Intelligence (BI) platforms and warehouses. Implement checks and rules to ensure data accuracy, consistency, and reliability across systems. Continuously monitor and refine data models and database performance for efficient querying and reporting. Maintain clear documentation of models, schemas, and data flows while adhering to data governance standards. Help design access controls and security measures to protect sensitive data. Develop and utilize Structured Query Language (SQL) queries for ad hoc analysis, troubleshooting, and data validation. Participate in Agile workflows across analysis, development, quality assurance (QA), and user acceptance testing (UAT) phases as a data subject matter expert. Build strong knowledge of business systems and data domains to support strategic initiatives.

Qualifications: Bachelor’s degree in computer science, a related field, or equivalent practical experience.7+ years of experience in data modeling, data warehousing, and ETL processes. Strong Hands-on experience of dimensional modeling, fact tables, star/snowflake schemas, slowly changing dimensions (SCDs), and tools like Erwin. Expertise with SQL (including Transact-SQL) and deep experience with relational database systems such as Microsoft SQL Server. Experience with data pipelines using ETL or Extract, Load, Transform (ELT) techniques and tools such as Azure Data Factory (ADF) to load data into analytics data marts, data warehouses and data lakes. Experience with analytics data platforms such as Azure Synapse Analytics, One Lake or Microsoft Fabric. Familiarity with Business Intelligence (BI) platforms such as Microsoft Power BI and Qlik Sense, and experience supporting enterprise reporting. Exposure to Python, PySpark, Databricks, or programming languages like Java or C# is a plus. Understanding of data governance principles, access controls, and data protection best practices.