BI Data Modeler

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, construct, and sustain conceptual, logical, physical, dimensional, and semantic data models.

• Convert business and analytical needs into scalable, reusable data models, standardized metrics, KPIs, calculations, and reporting definitions.

• Develop and oversee Power BI semantic models, dashboards, reports, and curated analytical datasets.

• Create calculations, queries, and data transformations utilizing DAX, SQL, and Power Query/M.

• Construct planning and analytical models that support prediction, scenario analysis, sensitivity analysis, and business decision-making.

• Profile, validate, reconcile, and test data for accuracy, consistency, quality, and analytical readiness.

• Enhance model performance, including storage modes, aggregations, partitions, incremental refresh, query performance, memory usage, and scalability.

• Integrate data from enterprise data warehouses, data lakes, APIs, and other sources in collaboration with data engineering and platform teams.

• Implement and uphold data security and governance practices, including Row-Level Security, Object-Level Security, sensitivity labeling, lineage, certification, and metric governance.

• Support production semantic models and datasets through monitoring, troubleshooting, root-cause analysis, and issue resolution.

• Apply source control, peer review, deployment, change management, and rollback practices.

• Prepare trusted datasets, metadata, metric definitions, and business context for AI, machine learning, semantic search, AI-powered assistants, and LLM-based analytics.

• Collaborate with technical and business stakeholders to gather requirements and maintain model diagrams, data dictionaries, user documentation, metric definitions, and support runbooks.

• Comply with Company policies, procedures, and requirements regarding compliance and Health, Safety, and Environment.

• Maintain consistent and reliable attendance.

• Perform additional duties as assigned.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Technology, Information Systems, Data Science, Data Analytics, Computer Engineering, or a related technical field, or equivalent relevant technical education and professional experience.

• 3-5 years of professional experience in business intelligence, data analytics, data modeling, semantic modeling, data warehousing, or a related data field.

• Practical experience in developing dimensional data models, including star and snowflake schema structures.

• Strong practical experience with Power BI, DAX, Power Query/M, and SQL.

• Experience with enterprise data warehouses, data lakes, or modern data platforms and the integration of data from various sources.

• Familiarity with data quality, testing, security, governance, lineage, and enterprise reporting practices.

• Experience with source control and structured development practices, including Git, peer review, environment promotion, and deployment pipelines.

• Strong analytical and problem-solving abilities, with the capacity to convey complex data concepts to both technical and non-technical business audiences.

• Experience with Databricks, Medallion Architecture, and Unity Catalog.

• Experience with semantic-layer or metrics technologies such as dbt, AtScale, Kyligence, or similar platforms.

• Experience supporting enterprise-scale self-service BI and contemporary cloud data architectures.

• Experience with planning, forecasting, scenario modeling, or advanced analytical use cases.

• Exposure to AI, machine learning, semantic search, LLM-based analytics, or preparing curated enterprise data for AI consumption.

• Familiarity with TMDL, XMLA endpoints, REST APIs, PowerShell, MDX, or BI/data platform automation.

• Relevant Microsoft, Databricks, cloud, data, analytics, or business intelligence certifications.

🏝️ Benefits

• Health insurance.

• Dental insurance.

• Vision insurance.

• Paid time off.

• Life insurance.

• 401(k) with a company match.

• Mental health coverage.

• Gender affirming benefits.

• Family building benefits.

• Paid parental leave.

• Associate discounts.

• Community involvement opportunities.

• Bonus or incentive plan eligibility.