Data Engineer - Data Platform & Integrations - Howard Energy Partners

At Howard Energy Partners, we believe that people build capability, capability drives performance, and performance, when guided by purpose, allows us to deliver energy that helps communities prosper. This role sits at the center of how we amplify that through data, automation, and the intelligent tools our teams will depend on for years to come.

Raw data is everywhere: in our systems, our sensors, our transactions. But data alone doesn't move the business. It has to be shaped into information, refined into evidence, and ultimately owned as knowledge before it becomes something a person can act on. That journey, from source to decision, is what this team is responsible for, and why the work matters

This is a hands-on engineering role on a small team. You will write code, ship pipelines, keep production healthy, and partner with people across Operations, IT, Finance, and the business to turn requirements into durable, reliable data products. The work is meaningful, the ownership is real, and the platform you help build will be a direct part of how Howard grows.

Duties & Responsibilities:

Data Pipeline Development & Integration

• Build and ship production-grade data pipelines and integrations on our Azure platform, connecting the systems that run the business: financial, operational, HR, measurement, and vendor data sources.
• Develop and maintain analytics-ready datasets for downstream consumers, gathering requirements from business stakeholders and validating that the logic reflects operational reality.
• Build and maintain integrations across enterprise systems, treating the data platform as a central integration point that grows in value as each connection is added.
• Participate in proof-of-concepts for new ingestion patterns, modeling approaches, or integrations that support AI and automation use cases, and help productionize the ones that work.

Platform Operations & Reliability

Operate what you build: monitor pipelines, keep them healthy, document runbooks, and follow root causes through to resolution.

Improve the platform as you go with better tests, better documentation, and better observability, so that what gets built stays built.

Occasionally support analytics needs such as Power BI datasets or lightweight Python outputs when it directly accelerates a data product delivery.

Stakeholder Partnership

Partner with departments throughout the company to understand what they need and translate that into technical solutions that reflect operational reality.

Explain technical concepts clearly to non-technical stakeholders, in the room and in writing.

Gather requirements directly, validate logic against real business conditions, and close the loop with confidence.

Continuous Improvement

Identify opportunities to improve consistency, reliability, and clarity across the data platform as the business grows.