Data & Analytics Engineer

Overview

Company Overview

Apex Service Partners (“Apex” or the “Company”) is a group of leading residential services businesses that conducts HVAC, plumbing and electrical work for residential homeowners. In this fragmented industry dominated by small and founder-owned businesses, the Company’s strategy is to execute significant organic growth initiatives and high-frequency M&A. This roll-up strategy necessitates an A+ data & analytics team.

Apex Service Partners was founded in 2019 with a mission to build a partnership of like-minded world-class service providers to build an industry leading national platform. Apex focuses on leveraging the power of people to build a strong network of industry leaders who can share resources, best practices, and expertise to deliver unparalleled service to customers and opportunities for employees.

The Company and its executive team are being backed by Alpine Investors (“Alpine”), a private equity firm that specializes in majority or full buyouts of founder-owned businesses and corporate carve- outs. Alpine specializes in middle-market companies (i.e., those with valuations up to $500 million), having invested in 50+ businesses since inception in 2001. Alpine recently closed its Fund IX at $4.5 billion in capital commitments.

Job Description – Data Engineer (Data & Analytics)

Mission of the Role:

Apex is looking for a Data Engineer who is eager to help build a world-class data and analytics organization. This individual will own the design and reliability of Apex's core data infrastructure from how data is generated and captured at the source, through how it moves, transforms, and triggers downstream action. This individual would be responsible for (i) Integrating data from various sources systems and maintain ingestion infrastructure, (ii) designing and automating real-time processes and workflows that act on that data (iii) growing into a genuine thought partner on how Apex's data infrastructure and automation capabilities should evolve to support Agentic AI-Driven systems.

In the near term, this role is about delivery, earning trust by shipping reliable pipelines, building event-based and streaming architectures, and standing up automated, agentic workflows that turn data events into real business actions (not just dashboards or reports). Over time this role is intended to grow into a role that builds a data platform to support Agentic AI including Ontologies, Vector Databases, MCP Servers, etc.  The right candidate is comfortable in the weeds of Python, event architecture, and API integration, while also thinking ahead to where data agents and AI-driven automation should go next.

Responsibilities:

• Design, build, and maintain event-driven data architectures, enabling real-time and near-real-time data flows across systems (Azure Event Hubs/Service Bus experience preferred).
• Develop and manage streaming data pipelines to support low-latency, near-real-time analytics and operational use cases.
• Build and maintain robust data ingestion pipelines in Python, sourcing data from APIs, databases, and streaming platforms.
• Integrate data between multiple APIs and internal systems, ensuring reliable, well-documented, and maintainable data flows.
• Design and build event-driven process automation, systems that detect a business event (e.g., a status change, a record update, a threshold being crossed) and automatically trigger downstream actions across other systems.
• Build agentic workflows that can interpret an event, decide on the appropriate action(s), and execute them via API calls with appropriate logging, error handling, and human-in-the-loop checkpoints where needed.
• Where relevant, apply graph database concepts for relationship-based data modeling desirable but not required for this role.
• Partner with the BI/analytics team to ensure upstream data structures support downstream semantic models and reporting needs.
• Own data quality and pipeline reliability end-to-end; nothing ships until accuracy has been verified.
• Contribute to the long-term data architecture roadmap as the function and business continue to scale.
• Manage multiple concurrent data engineering projects without losing momentum, maintaining clear priorities and consistent follow-through..

Experience:

• Bachelor's/master’s degree in computer science, Data Engineering, Information Technology, or a related field.
• 5+ years of experience in data engineering, with hands-on work designing and operating event-based architectures (Azure preferred, not mandatory).
• Demonstrated experience working with streaming or near-real-time data pipelines (e.g., Kafka, Event Hubs, Kinesis, Spark Streaming) is a strong plus.
• Strong proficiency in Python, with a focus on building data ingestion frameworks and pipelines. Spark is a plus but not mandatory.
• Proficiency in Python, including experience writing event-driven handlers or functions (e.g., via Azure Functions or AWS Lambda).
• Exposure to agentic or LLM-based automation frameworks (e.g., LangChain, Semantic Kernel) is a plus, especially where the system needs to decide the appropriate action rather than follow fixed rules.
• Exposure to graph databases (e.g., Neo4j, CosmosDB Gremlin API) is highly desirable but not a requirement candidate without this background will still be considered strongly.
• Experience integrating and orchestrating data across multiple APIs is required.
• Experience building or contributing to data agents or automated data workflows is preferred.
• Experience with event/messaging infrastructure such as Kafka, Azure Event Hubs, or Azure Service Bus, including familiarity with Change Data Capture (CDC) patterns for detecting source-system changes.
• Hands-on experience with a workflow orchestration tool (e.g., Azure Logic Apps, Airflow or similar tool) to encode conditional, multi-step automation logic.
• Experience building automation with reliability and safety in mind, error handling, logging/observability, and rollback-safe design for actions with real operational impact.
• Familiarity with the Microsoft Fabric/Azure ecosystem (OneLake, Lakehouses, Data Pipelines) is a plus.
• Experience working with Marketing Tech Stack data (attribution, campaign performance data, customer journey data) is a strong plus.

Personal Characteristics:

• Lives at the intersection of strategy and technology — can shape a conversation with a CFO and then turn around and earn the respect of an engineer.
• Analytical — finds meaning in numbers and pushes for data-driven decisions even when it's uncomfortable.
• Exceptional communicator — written and oral; says the right thing to the right audience without losing substance.
• Thrives managing multiple workstreams in a fast-moving environment; doesn't need perfect information to make a call.
• High standards — holds the team and the work to a bar that reflects well on the function.
• Strong work ethic with a demonstrated history of outworking peers.
• Resourceful — figures out how to get things done with what's in front of them.
• Thrives in a nimble, lean, unstructured, fast-paced entrepreneurial environment.
• Works collaboratively and energetically; lifts the people around them.
• Impeccable integrity and ethical standards.
• Self-aware, accepting, honest, open, and respectful of others.

Other:

Location: Tampa, FL

Compensation: Competitive

Other Benefits: medical, dental and vision coverage; unlimited PTO; 401(k) matching

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