Data & Analytics Engineer
JAMES M PLEASANTS COMPANY INC Greensboro, North Carolina, United States
Construction · 201-500 employees
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About the role
Build and support data ingestion and transformation pipelines, dimensional models, governed Power BI semantic models, and reports that support operational and executive decisions. Validate data quality, troubleshoot pipeline and refresh issues, define requirements and metrics with stakeholders, and follow governance, security, deployment, and documentation standards.
What they look for
Requirements
Candidates should have at least two years of relevant experience and practical SQL and Power BI skills, with knowledge of dimensional modeling, ETL/ELT, data validation, security, and source control. Strong candidates can deliver analytics solutions from source data through reporting; Microsoft Fabric experience, stakeholder-facing requirements work, and pipeline troubleshooting are preferred.
Full description
Role Summary
The Data & Analytics Engineer designs, builds, and supports data and reporting solutions that help drive business decisions across the organization. This role will be working with Microsoft Fabric, Power BI, SQL, and data pipelines to deliver trusted analytics, reliable data models, and actionable insights.
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 Technical Skills
- 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.
- 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.
- 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.
Requires periodic travel to the home office, located in Greensboro, NC.
