Fabric Data Engineer at Bioventus in Durham, NC

  • Company: Bioventus
  • Location: Durham, NC
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-30

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Job description

Are you ready to work for a more active world? At Bioventus, our business depends on developing our people. We invest in you and challenge you to be the best. We value our colleagues for their different perspectives and individual contributions, and our leaders listen. Our success rests on working together to achieve shared goals and rewards. Join a diverse team of global colleagues driven to help patients resume and enjoy active lives. The Fabric Data Engineer administers, governs, and continuously improves the Microsoft Fabric environment while designing reliable data pipelines in Microsoft Fabric and Azure Data Factory that integrate internal and external data sources. This role combines Fabric platform administration, data engineering, and advanced SQL development to deliver secure, scalable, observable, and high-performing analytics solutions. The individual establishes platform and development standards, optimizes capacity and workloads, develops and tunes SQL views and stored procedures, recommends indexing strategies, and partners with business and technical teams to improve data quality, performance, and operational reliability. Key Responsibilities: • Administer Microsoft Fabric capacities, workspaces, lakehouses, warehouses, OneLake, notebooks, Dataflows Gen2, pipelines, gateways, connections, access controls, and deployment pipelines. • Monitor capacity utilization, workload performance, refreshes, platform health; recommend configuration, scheduling, scaling/design improvements that balance reliability, performance, and cost. • Design, build, test, deploy, and support data pipelines and transformation workflows in Microsoft Fabric and Azure Data Factory for internal and external data sources. • Create and optimize T-SQL views, stored procedures, functions, and data-loading routines using execution plans, Query Store, statistics, indexing, locking, and workload analysis. • Perform SQL performance reviews, identify bottlenecks and expensive queries, recommend indexes, and validate improvements without introducing regressions or unnecessary maintenance overhead. • Design and maintain scalable lakehouse, warehouse, relational, and dimensional data structures; apply incremental loading, partitioning, parallelism, and reusable engineering patterns. • Implement standards for architecture, security, governance, data quality, lineage, source control, automated testing, CI/CD, release management, and technical documentation. • Diagnose and resolve pipeline, connectivity, refresh, access, capacity, and SQL performance issues; implement monitoring, alerting, runbooks, and root-cause corrective actions. • Partner with business, analytics, integration, infrastructure, and security teams to translate requirements into reliable data solutions and communicate service health and delivery status. • Lead Fabric and SQL platform improvement initiatives, including performance optimization, modernization, technical debt reduction, and workload migration. • Optimize data ingestion and transformation patterns for incremental loading, partitioning, parallelism, concurrency, data movement, and efficient use of Fabric capacity. • Maintain technical documentation for architecture, data flows, source-to-target mappings, standards, support procedures, dependencies, and operational ownership. • Holds oneself and others accountable to conduct business in a manner compliant with Bioventus’ Code of Compliance & Ethics, policies and procedures and internal controls applicable to their role. • All other duties or projects as assigned. Education and Experience (Knowledge, Skills & Abilities) • Bachelor’s degree in computer science, information systems, data engineering, or a related field, OR an equivalent combination of education and relevant experience (generally, 8 years combined education, certifications, and relevant experience may be considered). • 3+ years of progressive experience in data engineering, data warehousing, database development, or

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