Senior Data Engineer - Microsoft Fabric

Black & Veatch Family of Companies•Cary, NC

About The Position

The Senior Data Engineer will join Black & Veatch’s Digital & Data team, which works to digitally transform the company and advance its technology and data capabilities. The role is part of a strategic team of data scientists, engineers, developers, strategists, and technology professionals, and contributes to data initiatives across business units. The position is responsible for maintaining, building, and enhancing data engineering capabilities and the data development lifecycle. Work includes monitoring, optimization, automation, data maintenance, and support, as well as hands-on development with varied data volumes and a thorough understanding of the data lifecycle. The role focuses on scalable data engineering and integration, trusted enterprise data products, data quality and governance, reliable production operations, and data assets that support analytics and AI. The position requires a bachelor’s degree in computer science or a related field, or equivalent work experience, along with ten years of related experience. Hybrid or flexible work options may be offered after the first 90 days, subject to manager discretion, job performance, and work assignments.

Requirements

Bachelor’s degree in computer science or a related field, or equivalent work experience.
Ten years of related experience in addition to the education requirement.
Ability to complete applicable pre-employment onboarding requirements, which may include background checks, drug screening, and motor vehicle records searches.
Experienced with Agile methodology, ETL, data automation, job monitoring, data infrastructure, and data architecture.
Hands-on data development experience and a deep understanding of the data lifecycle, including work with large and small data volumes.

Nice To Haves

Eight or more years of enterprise data engineering experience designing, building, and supporting scalable production data solutions.
Advanced hands-on proficiency in SQL, Python, and Apache Spark/PySpark for data ingestion, transformation, and processing.
Hands-on experience with Microsoft Fabric or comparable modern cloud Lakehouse platforms, including Delta Lake and modern data integration patterns.
Strong data-modeling experience and development of trusted, reusable, consumption-ready data assets or Data Products.
Production experience implementing data quality, observability, troubleshooting, and root-cause analysis for data pipelines and data products.
Experience with Git, CI/CD, automated testing, modern engineering practices, technical leadership, and independently owning complex solutions.
Advanced hands-on experience with Microsoft Fabric, including OneLake, Lakehouse, Warehouse, Data Factory, Pipelines, Notebooks, and Spark workloads.
Experience designing and supporting enterprise Data Products and domain-oriented data architectures.
Experience building semantic models or reusable semantic assets for analytics and AI consumption.
Experience with Fabric Real-Time Intelligence, Eventstreams, streaming, or event-driven architectures.
Experience with Microsoft Purview, metadata management, lineage, classification, and enterprise data catalog capabilities.
Experience with Power BI semantic models or related analytical consumption technologies.
Familiarity with Azure AI Foundry, Azure OpenAI, RAG, vector search, embeddings, or AI-ready data patterns.
Experience implementing advanced data observability for freshness, completeness, schema drift, volume anomalies, and data reliability.
Experience working within Data Product, Data Mesh, platform engineering, or domain-oriented operating models.

Responsibilities

Design, build, and optimize scalable data engineering and integration solutions using Microsoft Fabric, OneLake, Delta Lake, Spark, SQL, and related Microsoft technologies across batch, near-real-time, and event-driven workloads.
Develop and maintain trusted enterprise data products, Lakehouse and Data Warehouse solutions, and reusable datasets for analytics, reporting, digital solutions, and AI use cases.
Design data models and semantic assets that standardize business definitions, shared entities, reference data, and transformation logic across business domains.
Implement data quality, governance, privacy, security, metadata, lineage, and access controls, including automated validation, reconciliation, and quality gates.
Establish data observability, monitoring, and reliability practices to support data-product performance, availability, accuracy, resiliency, and cost efficiency.
Lead production support and complex troubleshooting, including root-cause analysis, incident resolution, recovery procedures, and preventive improvements for business-critical data solutions.
Apply DevOps and engineering practices, including Git, automated testing, CI/CD, code reviews, reusable frameworks, and automation.
Provide technical leadership for modern data and AI solutions, develop AI-ready data assets for RAG, agents, Copilot, and advanced analytics, mentor engineers, partner across business and technology teams, and evaluate emerging Microsoft Fabric capabilities.