Data Pipeline & Connectivity Engineer

? Connectivity & Data Ingestion

• Design and implement robust ingestion pipelines across highly fragmented environments (multiple ERPs, isolated networks, legacy systems)

• Build connectivity across:

• ERP systems (e.g., Great Plains, SAP, Infor, custom systems)

• APIs, flat files, streaming sources, and third-party platforms

? Must-Have Experience

• 5-10+ years in data engineering / pipeline engineering

• Deep hands-on experience with:

• Databricks (required)

• PySpark

• Delta Lake

Proven experience building:

• Data pipelines across multiple disconnected systems
• Scalable ingestion frameworks

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? Strongly Preferred

• Experience in complex, multi-entity environments (PE-backed, M&A, roll-ups)

• ERP data integration experience:

• Great Plains, SAP, Infor, NetSuite, etc.

Experience with:

• AWS or Azure data ecosystems
• API integrations and event-based pipelines
• Data orchestration tools, * Builder mindset - thrives in greenfield + messy environments
• Comfortable operating with incomplete data and evolving requirements
• Can own problems end-to-end, not just execute tickets
• Balances speed with scalable architecture

We are a rapidly growing, private equity-backed services platform operating across dozens of acquired business units. Our environment consists of 50+ disconnected systems and ERPs, each operating independently across separate networks. We are building a modern, Databricks-first data and AI platform to unify operations, enable real-time insights, and power next-generation AI use cases., This is a foundational engineering role focused on solving one of the hardest problems in modern data: connecting fragmented systems into a scalable, governed data platform. You will own the design and build of data pipelines, ingestion frameworks, and connectivity patterns that bring together disparate environments into Databricks-laying the groundwork for data products, analytics, and AI. This is not a support role. This is a hands-on builder role for someone who wants to architect and implement at scale.