Data Engineer

Legence (Nasdaq: LGN) is a leading provider of engineering, consulting, installation, and maintenance services for mission-critical systems in buildings. The company specializes in designing, fabricating, and installing complex HVAC, process piping, and other mechanical, electrical, and plumbing (MEP) systems - enhancing energy efficiency, reliability, and sustainability in new and existing facilities. Legence also delivers long-term performance through strategic upgrades and holistic solutions.

Serving some of the world’s most technically demanding sectors, Legence counts over 60% of the Nasdaq-100 Index among its clients.

We are seeking a highly skilled Data Engineer to design, develop, and maintain scalable data solutions that support analytics, reporting, and business operations across the organization. This hands-on role requires expertise in data architecture, data integration, cloud platforms, and modern data engineering practices.

The ideal candidate will be responsible for building robust data pipelines, optimizing data platforms, and ensuring the availability, quality, and reliability of enterprise data. This role will interact directly with business stakeholders and end users to gather requirements, support testing efforts, and deliver scalable solutions.

This position is remote, with preference given to candidates located near a Legence office location.

• Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, Python, SQL, and related technologies.
• Develop and optimize enterprise data models utilizing dimensional modeling techniques, including star and snowflake schemas.
• Implement and manage data warehouses, data lakes, and lakehouse architectures.
• Integrate data from ERP systems, APIs, cloud platforms, databases, and third-party applications.
• Build scalable frameworks for data validation, monitoring, and quality assurance.
• Establish and maintain data governance standards, documentation, and lineage.
• Configure and support cloud-based data platforms and environments.
• Develop, optimize, and maintain complex SQL queries, stored procedures, and data transformations.
• Improve performance and reliability of data pipelines through optimization and monitoring.
• Implement security controls and access management to protect enterprise data.
• Automate data processing workflows and scheduled jobs.

• Partner with business stakeholders to understand data requirements and translate them into technical solutions.
• Support solution testing, deployment, and ongoing maintenance activities.
• Provide technical guidance and recommendations regarding data architecture and platform design.
• Document technical designs, data flows, and operational procedures.

• 3+ years of hands-on Data Engineering experience.
• Strong SQL skills, including database design, performance tuning, and query optimization.
• Experience building and maintaining ETL/ELT pipelines.
• Experience with Azure Data Factory, Microsoft Fabric, Azure Synapse Analytics, Azure SQL Database, or similar cloud-based data platforms.
• Proficiency with Python for data transformation, automation, or integration tasks.
• Solid understanding of data warehousing concepts, dimensional modeling, and data architecture best practices.
• Experience integrating data from APIs, enterprise applications, and cloud services.

• Strong understanding of data modeling techniques and relational database concepts.
• Experience performing data profiling, validation, and quality assessments.
• Ability to translate business requirements into scalable technical solutions.
• Understanding of data…