Data & Analytics Engineer
Summary
Onsite data-focused generalist at an equipment company in Greensboro, NC, building and supporting analytics on Microsoft Fabric and Power BI: roughly 45% Power BI dashboards and semantic models, 35% data engineering pipelines, plus business analysis and light Python/PowerShell automation.
Position intent: Hire a data-focused generalist who can build and support modern analytics solutions using Microsoft Fabric, Power BI, SQL, dimensional modeling, data pipelines, and governed semantic models.
Recommended Work Emphasis
Focus Area | Target Emphasis | Primary Outcomes |
Data Engineering | 35% | Reliable ingestion, transformation, modeling, pipelines, quality controls, and reusable curated data. |
Analytics & Power BI | 45% | Trusted semantic models, dashboards, operational reporting, and decision support. |
Business Analysis | 15% | Well-defined requirements, metric definitions, validation, documentation, and user acceptance testing. |
Supporting Automation / Code | 5% | Light Python, PowerShell, APIs, or Power Automate used to extend and automate analytics workflows. |
What This Role Is Not
- Not a full-stack software engineering position.
- Not primarily focused on mobile, web, or enterprise application development.
- Not limited to building report visuals without responsibility for the underlying data and business logic.
- Not a purely administrative Power BI role.
Core Responsibilities
Responsibility Area | Expected Contribution |
Fabric Data Engineering | Develop and support ingestion and transformation processes using Fabric pipelines, Dataflows Gen2, lakehouses, warehouses, notebooks, or other appropriate Fabric components. |
Data Modeling | Create and maintain dimensional models, curated analytical tables, relationships, conformed dimensions, and reusable business logic. |
Semantic Models | Build and support governed Power BI semantic models, including measures, relationships, refresh design, security, naming standards, and documentation. |
Power BI Analytics | Develop clear, useful, performant reports and dashboards that answer defined business questions and support operational and executive decision making. |
Data Quality | Validate source-to-report results, identify data issues, document reconciliation logic, and implement repeatable data-quality checks. |
Pipeline Operations | Monitor refreshes and pipelines, troubleshoot failures, improve reliability, and document support procedures. |
Requirements & Metrics | Work with stakeholders to define requirements, business rules, KPIs, acceptance criteria, and authoritative metric definitions. |
Governance & Deployment | Follow workspace, security, testing, change-control, release, lineage, and production-readiness standards. |
Documentation & Enablement | Create technical documentation, data dictionaries, solution notes, lineage descriptions, user guidance, and knowledge-transfer materials. |
Required Technical Skills
- Strong SQL/T-SQL skills, including joins, common table expressions, aggregations, window functions, data validation, and query troubleshooting.
- Python or PySpark for data preparation, validation, notebooks, or automation.
- Hands-on Power BI development experience, including Power Query, semantic models, interactive report design, publishing, and refresh support.
- Understanding of dimensional modeling, including fact tables, dimension tables, star schemas, grain, keys, and slowly changing dimensions.
- Understanding of ETL and ELT concepts, data ingestion, transformation, orchestration, dependencies, and error handling.
- Ability to reconcile data from source systems through transformation layers to published reports.
- Experience creating clear technical documentation and translating business definitions into governed analytical logic.
- Working knowledge of security concepts that affect analytics, including access management and row-level security.
- Basic Git or Azure DevOps source-control practices.
- Strong communication with technical and non-technical audiences.
Preferred Microsoft Fabric Experience
- Fabric workspaces, capacities, items, and deployment concepts.
- Lakehouse and Warehouse design and support.
- Data Factory pipelines and Dataflows Gen2.
- Fabric notebooks and Spark or Python for data engineering tasks.
- OneLake concepts, shortcuts, and medallion-style data organization.
- Direct Lake and Import semantic-model considerations.
- Monitoring Hub, refresh troubleshooting, lineage, and operational support.
- Deployment pipelines, source control, or structured development and release practices.
Preferred Power BI Experience
- Advanced calculation patterns.
- Power Query and reusable transformation logic.
- Semantic-model performance optimization and model simplification.
- Row-level security and testing across business entities or user groups.
- Workspace organization, Power BI apps, deployment, and access management.
- Report usability, accessibility, visual consistency, and performance optimization.
- Shared semantic models and thin-report development patterns.
Supporting Coding Skills
Not necessary, but nice to have. Will use these skills but I can teach them if not known already.
- PowerShell for administration or repeatable support tasks.
- Ability to work with REST APIs, JSON, authentication concepts, and configuration values.
- Ability to read, troubleshoot, and adapt existing code without needing to be a full-stack developer.
Business and Professional Skills
- Ability to translate a business problem into data requirements, model requirements, metrics, and reporting outcomes.
- Detail-oriented approach to data reconciliation, testing, and quality assurance.
- Ability to challenge unclear requirements and ask effective follow-up questions.
- Comfort managing several priorities across development, troubleshooting, stakeholder support, and documentation.
- Curiosity, adaptability, and willingness to learn as the Fabric environment and analytics program mature.
Experience Profile
Level | Desired Background |
Minimum | Two or more years of relevant experience in data analytics, business intelligence, data engineering, data warehousing, or a closely related field; practical Power BI and SQL experience. |
Strong Candidate | Demonstrated experience building complete analytics solutions from source data through transformation, modeling, semantic models, and Power BI delivery. |
Ideal Candidate | Hands-on Microsoft Fabric experience, enterprise Power BI support, dimensional modeling, pipeline troubleshooting, governance, security, and stakeholder-facing requirements work. |
Skills
- Acceptance Criteria
- Accessibility
- Analytics
- API
- Authentication
- Automation
- Azure
- Azure Data Factory
- Azure DevOps
- Business Intelligence
- Data Analytics
- Data Engineering
- Data Ingestion
- Data Modeling
- Data Pipelines
- Data Quality
- Data Warehousing
- DevOps
- Dimensional Modeling
- ELT
- ETL
- Git
- JSON
- Lakehouse
- Microsoft Fabric
- Power Automate
- Power Query
- Power BI
- PowerShell
- PySpark
- Python
- REST
- Spark
- SQL
- SQL Server