Business Intelligence & Data Engineer

DuraServ Corp•Coppell, TX

1d•Onsite

About The Position

DuraServ is seeking an experienced Business Intelligence & Data Engineer to own the enterprise data and analytics architecture. The role designs, builds, documents, and supports enterprise data and analytics solutions, including scalable data pipelines, data warehouse models, and executive dashboards that provide actionable insights across the organization. The successful candidate will partner with business leaders and technical teams to transform operational data into business intelligence, using platforms and technologies such as Microsoft Fabric, Azure Data Factory, Azure SQL, Microsoft Dynamics 365 Field Service, Business Central, Dataverse, Power BI, SQL, and DAX. The position owns enterprise data integration and semantic-modeling strategies, governs the data platform’s architecture and standards, and provides technical leadership for analytics initiatives. It includes platform performance and capacity management, production support and incident escalation, and guidance and mentoring for data, BI, application, and consulting resources. The position has no supervisory responsibilities. The work is performed in an office environment and involves prolonged periods sitting at a desk and working on a computer. The role may require lifting up to 15 pounds at times. No planned business travel is required. A bachelor’s degree in computer science, Information Systems, Engineering, Data Analytics, or equivalent experience may be considered. The position requires 7+ years of progressive experience in data engineering, business intelligence, data warehousing, analytics engineering, or related disciplines; 5+ years designing and delivering enterprise data and analytics solutions using SQL, dimensional modeling, and Power BI; and 3+ years with cloud data platforms such as Microsoft Fabric, Azure Data Factory, Azure SQL, Data Lake, Lakehouse, or comparable technologies. Experience with Dynamics 365, Business Central, Dataverse, ERP, field service, or operational business data is preferred.

Requirements

Bachelor’s degree in computer science, Information Systems, Engineering, Data Analytics, or equivalent experience may be considered.
7+ years of progressive experience in data engineering, business intelligence, data warehousing, analytics engineering, or related disciplines.
5+ years of experience designing and delivering enterprise data and analytics solutions using SQL, dimensional modeling, and Power BI.
3+ years of experience with cloud data platforms such as Microsoft Fabric, Azure Data Factory, Azure SQL, Data Lake, Lakehouse, or comparable technologies.
Strong expertise developing complex DAX measures and calculations and enterprise ETL processes.
Experience with Fabric notebooks, Spark, and Python for data engineering workloads.
Experience with Azure Data Factory or Microsoft Fabric Data Factory.
Experience with Azure SQL or SQL Server, Dataverse, and designing star-schema data warehouse models.
Experience with Microsoft Dynamics 365 Field Service and Business Central.
Strong understanding of data warehousing concepts, dimensional modeling, data observability, lineage, cataloging, and metadata management.
Experience with data security, classification, access control, RLS, OLS, and auditing.
Experience with SQL performance tuning and query optimization.
Excellent troubleshooting, communication, and problem-solving skills.
Demonstrated experience defining technical standards, leading architecture or design reviews, optimizing cloud data workloads, and delivering analytics solutions across multiple business functions.

Nice To Haves

Experience with Dynamics 365, Business Central, Dataverse, ERP, field service, or operational business data is preferred.

Responsibilities

Own the design and evolution of enterprise data integration architecture across Microsoft Fabric, Azure Data Factory, Dynamics 365, Dataverse, Business Central, and other enterprise platforms.
Establish reusable ingestion, orchestration, observability, error-handling, and recovery patterns for batch and near-real-time workloads.
Define and govern enterprise medallion architecture standards for ingestion, transformation, lineage, retention, reconciliation, quality, and publication across bronze, silver, and gold data products.
Establish an enterprise data-quality framework with measurable rules, ownership, monitoring, exception management, root-cause analysis, and remediation processes for critical data domains.
Partner with business and technology leaders to turn strategic objectives into a prioritized enterprise data and analytics roadmap, target-state architecture, and scalable data products.
Define and enforce engineering standards for source control, CI/CD, automated testing, release management, infrastructure configuration, documentation, observability, and production support.
Own the enterprise semantic-modeling strategy and establish certified, reusable data models with consistent dimensions, calculations, KPIs, and business definitions across Finance, Operations, Service, and executive reporting.
Establish dimensional-modeling, Direct Lake, Import, Direct Query, composite-model, calculation-group, aggregation, and DAX performance standards based on workload requirements.
Lead platform performance and capacity management, including workload monitoring, refresh optimization, query tuning, storage strategy, capacity planning, licensing analysis, and cloud cost optimization.
Define and govern Power BI and Microsoft Fabric workspace architecture, deployment patterns, access models, Row-Level Security, Object-Level Security, endorsement, certification, release controls, and environment segregation.
Serve as senior technical advisor for enterprise data and analytics initiatives, facilitating architecture decisions, KPI-definition workshops, data-design reviews, and prioritization discussions.
Provide advanced technical escalation and root-cause leadership for high-impact data-platform incidents, and establish monitoring, support documentation, service expectations, and preventive controls.
Provide technical leadership through architecture reviews, engineering standards, code reviews, design guidance, knowledge-sharing, and mentoring of data, BI, application, and consulting resources.