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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining data models, including dimensional and semantic models, while leveraging tools like Power BI, DAX, and SQL for data analytics and reporting. Proficient in data governance, quality assurance, and integrating diverse data sources to support business intelligence initiatives.
Highest-signal resume keywords
Power BI DevelopmentDAX ProgrammingData ModelingData GovernanceSQL Querying
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ModelingDAXSQLPower Query/MDimensional Data ModelsData Quality TestingData IntegrationScenario AnalysisSemantic ModelingData Transformation
Soft Skills
Analytical SkillsProblem-SolvingCommunication
Tools & Technologies
Power BIDatabricksGitAPIsTMDLXMLA EndpointsMDXBI Automation
Certifications & Qualifications
Microsoft CertificationsDatabricks CertificationsBusiness Intelligence Certifications
Industry Keywords
Business IntelligenceData AnalyticsData WarehousingEnterprise ReportingCloud Data ArchitecturesAIMachine LearningSemantic Search
Tech Stack
Tools & technologiesCloudSQLUnity
About the role
Key responsibilities & impact- Design, build, and maintain conceptual, logical, physical, dimensional, and semantic data models
- Translate business and analytical requirements into scalable, reusable data models, standardized metrics, KPIs, calculations, and reporting definitions
- Develop and maintain Power BI semantic models, dashboards, reports, and curated analytical datasets
- Create calculations, queries, and data transformations using DAX, SQL, and Power Query/M
- Build planning and analytical models supporting prediction, scenario analysis, sensitivity analysis, and business decision-making
- Profile, validate, reconcile, and test data for accuracy, consistency, quality, and analytical readiness
- Optimize 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 with data engineering and platform teams
- Implement and support 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
- Partner with technical and business stakeholders to capture requirements and maintain model diagrams, data dictionaries, user documentation, metric definitions, and support runbooks
- Adhere to Company compliance and Health, Safety and Environment policies, procedures, and requirements
- Maintain regular and reliable attendance
- Perform other duties as assigned
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Information Technology, Information Systems, Data Science, Data Analytics, Computer Engineering, or a related technical subject area, 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
- Hands-on experience developing dimensional data models, including star and snowflake schema structures
- Strong hands-on experience with Power BI, DAX, Power Query/M, and SQL
- Experience with enterprise data warehouses, data lakes, or modern data platforms and integrating data from different sources
- Working knowledge of 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 skills, with ability to communicate complex data concepts to technical and non-technical business customers
- 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 modern 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
Comp & perks- 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