Data Engineer

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.

Position Overview

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.

Key Responsibilities

• 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.

Required Qualifications

• 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 governance, metadata management, and data lineage principles.

• Strong problem-solving skills and a hands-on, solution-oriented mindset.
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.
• Detail-oriented with a commitment to code quality, testing, and documentation.
• Demonstrated ability to leverage automation and AI-enabled tools to improve development efficiency.

Preferred Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• Microsoft DP-203 (Azure Data Engineer Associate) certification or equivalent.
• Experience with Databricks, Spark, or PySpark.
• Familiarity with Git, Azure DevOps, and CI/CD pipelines.
• Experience working with ERP, operational, financial, or construction-related datasets.
• Experience developing data lake or lakehouse architectures.
• Knowledge of data science concepts, machine learning workflows, or predictive analytics.

Technical Environment

• Microsoft Fabric
• Azure Data Factory
• Azure Synapse Analytics
• Azure SQL Database
• Azure Data Lake Storage
• SQL Server
• Python
• Databricks (preferred)
• Git / Azure DevOps
• APIs and Cloud Integration Services

This is a hands-on technical role requiring daily interaction with data, code, integrations, and cloud-based data platforms. The ideal candidate thrives in environments where they can build scalable solutions from the ground up and take ownership of the full data lifecycle.

Base salary: $105,000-$120,000 per year. This role is also eligible for an annual performance‑based bonus. Bonus eligibility and payout are determined by role, individual performance, and company performance, and are not guaranteed.

Unable to provide sponsorship for this position.