- A leading commercial HVAC services platform with a large North American footprint, headquartered in Charlotte and operating across a highly distributed network of service businesses
- A PE-backed growth environment focused on modernizing its data infrastructure and creating greater scalability, visibility, and consistency across the enterprise
- A decentralized operating model with multiple locations, systems, ERP platforms, and isolated data environments
- A growing data engineering team building and supporting centralized data pipelines and connectivity into the Databricks environment
- A collaborative data and AI organization laying the technical foundation for enterprise reporting, analytics, and future AI-enabled business use cases
LOCATION
- Charlotte, NC (Uptown) – Hybrid (3 days on-site)
WHAT THEY OFFER YOU
- Opportunity to play a hands-on role in a major enterprise data modernization initiative
- Direct ownership of data connectivity, ingestion, monitoring, and pipeline management within a growing Databricks environment
- Chance to solve complex engineering challenges across a distributed, multi-location organization with numerous source systems
- Technical work that directly supports improved reporting, analytics, and AI capabilities across the business
- Exposure to a fast-moving, PE-backed organization where scalability, reliability, and practical execution are highly valued
WHY THIS ROLE IS IMPORTANT
- Builds and supports reliable data pipelines that ingest information from multiple ERP systems, applications, databases, and operating locations into Databricks
- Strengthens connectivity between disconnected source environments and the organization’s centralized data platform
- Monitors pipeline performance, identifies failures or data-quality issues, and implements solutions that improve reliability and observability
- Helps maintain current ingestion processes while supporting the transition toward a more scalable and standardized target-state architecture
- Partners with data architecture, analytics, infrastructure, and business teams to ensure data is accessible, accurate, and available for downstream use
- Reduces technical bottlenecks that impact enterprise reporting, analytics, and future AI initiatives
THE BACKGROUND THAT FITS
- Strong hands-on experience developing, deploying, and supporting data pipelines within Databricks
- Experience with Databricks technologies and concepts such as Delta Lake, notebooks, workflows, jobs, clusters, and medallion architecture
- Proficiency with Python, PySpark, and SQL for data ingestion, transformation, and pipeline development
- Experience connecting Databricks to a variety of source systems, including relational databases, ERP platforms, APIs, files, and on-premise environments
- Understanding of ETL and ELT design patterns, data orchestration, incremental loading, and pipeline dependency management
- Experience monitoring production pipelines, troubleshooting failures, and improving data quality, performance, and reliability
- Familiarity with cloud-based data environments and services within Azure, AWS, or a comparable platform
- Ability to work across data engineering, networking, infrastructure, MSP, and application teams to resolve complex connectivity issues
- Experience operating in a distributed, multi-location, or multi-ERP business environment is strongly preferred
- Background in HVAC, field services, construction, facilities services, or another decentralized service organization would be a plus
