Senior Data Engineer - Microsoft Fabric

PJ Dick-Trumbull-Lindy Group • Pittsburgh, PA

3d • Hybrid

About The Position

We are seeking an experienced Senior Data Engineer to design, build, and optimize the enterprise data platform that powers analytics, reporting, and AI initiatives across PJ Dick, Trumbull, and The Lindy Group. This role will lead the design and implementation of modern data solutions using Microsoft Fabric, Azure services, and industry best practices for data engineering. The ideal candidate will possess extensive experience developing large-scale data pipelines, ETL/ELT processes, data models, and analytics platforms that support business-critical decision making. You will work closely with business leaders, application developers, data analysts, and external partners to transform data into a strategic asset. This position offers the opportunity to shape the company's long-term data architecture.

Requirements

• Minimum 7 years of professional Data Engineering experience supporting enterprise-scale environments.
• Minimum 1 years of hands-on Microsoft Fabric experience in production environments.
• Demonstrated experience designing and supporting large-scale data platforms and analytics ecosystems.
• Proven experience delivering end-to-end data engineering solutions from requirements through production deployment.
• Deep expertise with: Fabric Data Factory, Fabric Lakehouses, Fabric Warehouses, Semantic Models, OneLake, Spark Notebooks, Data Pipelines, Real-Time Analytics, Dataflows Gen2.
• Advanced SQL development and optimization.
• Strong ETL/ELT development experience.
• Experience working with large datasets and complex data transformations.
• Expertise in data modeling, dimensional modeling, and data warehousing methodologies.
• Experience building resilient, scalable, and automated pipelines.
• Experience converting non-relational or document-based data sources, including NoSQL and legacy platforms, into normalized relational schemas.
• Comfortable reverse-engineering data structures and tracing data discrepancies back to root cause in systems with limited or no formal documentation.
• Strong experience with: Azure SQL Database, Azure Data Factory, Azure Storage, Azure Functions, Azure Key Vault, Azure Monitor, Entra ID.
• Strong proficiency in Python.
• Experience with Spark and PySpark.
• Experience working with REST APIs and integration frameworks.
• Source control experience using Git, Azure DevOps, or Bitbucket.
• Experience implementing CI/CD for data engineering solutions.
• Ability to translate business requirements into scalable technical solutions.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Experience working directly with both technical and non-technical stakeholders.
• Ability to manage multiple priorities and projects simultaneously.
• Ability to scope, estimate, and deliver against committed timelines, with proactive communication when priorities or scope shift.
• Comfortable operating in an iterative delivery model where business stakeholders remain engaged throughout the build and requirements evolve as the work takes shape.

Nice To Haves

• Experience with construction, engineering, manufacturing, or professional services organizations.
• Experience integrating ERP platforms such as CMiC or similar enterprise systems.
• Experience with Power BI administration and enterprise reporting environments.
• Knowledge of data governance frameworks and regulatory compliance requirements.
• Experience supporting AI, machine learning, and advanced analytics initiatives.
• Prior experience serving as a technical lead or mentoring other data engineers.

Responsibilities

• Design, implement, and maintain enterprise data solutions using Microsoft Fabric.
• Build and manage Fabric Lakehouses, Warehouses, Semantic Models, and Data Factory Pipelines.
• Develop scalable data architectures that support reporting, analytics, machine learning, and AI initiatives.
• Optimize Fabric workloads for performance, scalability, governance, and cost management.
• Design, build, and maintain complex ETL and ELT pipelines that ingest data from ERP, project management, financial, operational, and external systems.
• Develop automated data integration processes utilizing Fabric Data Factory, Azure Data Factory, Spark notebooks, and APIs.
• Ensure data quality, reliability, lineage, and governance throughout the data lifecycle.
• Serve as a primary technical resource for diagnosing and resolving pipeline failures, data quality issues, and reporting discrepancies, often working backward from a broken output to identify root cause across ingestion, transformation, and delivery layers.
• Design and maintain enterprise data models that support operational and executive reporting.
• Transform structured and unstructured data into analytics-ready datasets.
• Collaborate with BI developers and analysts to build semantic models and Power BI reporting solutions.
• Establish standards for data architecture, metadata management, and master data management.
• Integrate Fabric solutions with Azure SQL Database, Azure Storage, Cosmos DB, Azure Functions, API Management, and other Azure services.
• Secure data exchange processes utilizing Entra ID, Key Vault, and Azure networking services.
• Develop data ingestion frameworks from cloud, on-premises, SaaS, and third-party platforms.
• Work with our security team to implement data governance, retention, and compliance requirements.
• Document architecture, operational procedures, and technical standards.
• Mentor team members and promote data engineering best practices across the organization.

Benefits

• Lead the modernization of a rapidly growing enterprise data platform.
• Shape the future of analytics, reporting, and AI across three industry-leading construction organizations.
• Work with modern Microsoft technologies including Fabric, Azure, Power BI, and AI solutions.
• Collaborate with business leaders who value data-driven decision making.
• Be part of an organization consistently recognized as one of Pittsburgh's Best Places to Work.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior