Data & Analytics Engineer

JAMES M PLEASANTS COMPANY INC•Greensboro, NC

19h

About The Position

The Data & Analytics Engineer builds and supports modern analytics solutions using Microsoft Fabric, Power BI, SQL, dimensional modeling, data pipelines, and governed semantic models. The role combines data engineering, analytics and Power BI development, business analysis, and supporting automation. Its emphasis is on delivering reliable data ingestion and transformation, reusable curated data, trusted semantic models and dashboards, and decision support. The role is not primarily focused on full-stack, mobile, web, or enterprise application development, nor is it limited to report visuals or Power BI administration. The engineer develops and supports Fabric ingestion and transformation processes; creates dimensional models, curated analytical tables, and reusable business logic; builds governed Power BI semantic models; and develops useful, performant reports and dashboards. The role also includes data validation, pipeline monitoring and troubleshooting, stakeholder requirements and metric definition, governance and deployment practices, documentation, and user enablement. The position requires strong SQL/T-SQL, Python or PySpark, practical Power BI development, knowledge of dimensional modeling and ETL/ELT concepts, data reconciliation, technical documentation, analytics-related security, basic source control, and communication with technical and non-technical audiences. Relevant experience is two or more years in analytics, business intelligence, data engineering, data warehousing, or a closely related field. Microsoft Fabric, advanced Power BI, and supporting coding skills are preferred or beneficial.

Requirements

Two or more years of relevant experience in data analytics, business intelligence, data engineering, data warehousing, or a closely related field, with practical Power BI and SQL experience.
Strong SQL/T-SQL skills, including joins, common table expressions, aggregations, window functions, data validation, and query troubleshooting.
Python or PySpark skills 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 analytics-related security concepts, including access management and row-level security.
Basic Git or Azure DevOps source-control practices.
Strong communication with technical and non-technical audiences.
Ability to translate business problems 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.

Nice To Haves

Hands-on Microsoft Fabric experience, including workspaces, capacities, items, and deployment concepts.
Experience designing and supporting Fabric lakehouses and warehouses.
Experience with Data Factory pipelines and Dataflows Gen2.
Experience with Fabric notebooks and Spark or Python for data engineering tasks.
Familiarity with OneLake concepts, shortcuts, and medallion-style data organization.
Understanding of Direct Lake and Import semantic-model considerations.
Experience with Monitoring Hub, refresh troubleshooting, lineage, and operational support.
Experience with deployment pipelines, source control, or structured development and release practices.
Advanced Power BI calculation patterns.
Power Query and reusable transformation logic experience.
Experience optimizing semantic-model performance and simplifying models.
Experience with row-level security and testing across business entities or user groups.
Experience with workspace organization, Power BI apps, deployment, and access management.
Knowledge of report usability, accessibility, visual consistency, and performance optimization.
Experience with 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.
Demonstrated experience building complete analytics solutions from source data through transformation, modeling, semantic models, and Power BI delivery.
Enterprise Power BI support, dimensional modeling, pipeline troubleshooting, governance, security, and stakeholder-facing requirements experience.

Responsibilities

Develop and support ingestion and transformation processes using Fabric pipelines, Dataflows Gen2, lakehouses, warehouses, notebooks, or other appropriate Fabric components.
Create and maintain dimensional models, curated analytical tables, relationships, conformed dimensions, and reusable business logic.
Build and support governed Power BI semantic models, including measures, relationships, refresh design, security, naming standards, and documentation.
Develop clear, useful, performant reports and dashboards that answer business questions and support operational and executive decision making.
Validate source-to-report results, identify data issues, document reconciliation logic, and implement repeatable data-quality checks.
Monitor refreshes and pipelines, troubleshoot failures, improve reliability, and document support procedures.
Work with stakeholders to define requirements, business rules, KPIs, acceptance criteria, and authoritative metric definitions.
Follow workspace, security, testing, change-control, release, lineage, and production-readiness standards.
Create technical documentation, data dictionaries, solution notes, lineage descriptions, user guidance, and knowledge-transfer materials.

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