Location: Charlotte, NC (Hybrid preferred; open to remote for the right candidate; likely out of the services business of use to connecting many disparate systems via Databricks / P.E. Roll up situation)
Compensation: Low 200''s + base + bonus + equity
Company Overview
Our client is a rapidly scaling, private equity-backed services platform growing through acquisition. With 50+ operating companies and a highly decentralized environment, the organization is undergoing a major transformation to unify data, enable AI, and drive operational excellence across the enterprise.
Today, data exists across dozens of disconnected ERP systems and environments. The mandate is clear: centralize, govern, and activate data at scale using Databricks as the core platform.
The Opportunity
This is a hands-on Director of Data Engineering role for a builder—someone who can operate as both architect and player-coach.
You will own the design and execution of the enterprise data platform, bringing together fragmented systems into a scalable, governed, and AI-ready ecosystem. This is not a pure leadership role—you will be expected to write code, build pipelines, and lead from the front.
You will play a critical role in establishing the foundation for:
- Enterprise data consolidation
- Data product development
- AI/ML enablement and LLM integration
What You’ll Own
Data Platform Architecture & Build (Hands-On)
- Design and implement a Databricks-first data platform on AWS
- Build and operationalize medallion architecture (bronze, silver, gold layers)
- Develop scalable, reusable data pipelines across 50+ disconnected systems
- Standardize ingestion patterns across ERP systems (e.g., Great Plains/WinSoft and others)
- Write production-grade code in Python/SQL within Databricks
Data Integration & Connectivity
- Solve for highly fragmented, non-standard environments across acquired companies
- Build frameworks for integrating data across isolated networks and systems
- Establish scalable ingestion strategies (batch + streaming where applicable)
Data Products & Business Enablement
- Partner with business stakeholders to create trusted, governed data products
- Enable operational reporting and real-time insights
- Support downstream tools (Power BI, analytics layers, etc.)
AI & Advanced Analytics Enablement
- Lay the foundation for AI/ML and LLM use cases within Databricks
- Support development of an LLM gateway and AI consumption layer
- Collaborate with AI leadership on use-case prioritization and execution
Governance & Operating Model
- Help establish and participate in a data governance committee
- Define standards for:
- Data quality
- Data ownership
- Access controls & compliance
- Align platform decisions to business outcomes, not just technical elegance
Leadership (Player-Coach)
- Lead and mentor a small but growing team of:
- Data engineers
- Integration specialists
- Analytics/BI resources
- Set engineering standards and best practices
- Remain deeply involved in hands-on delivery
What You Bring
Core Technical Experience
- Deep, hands-on experience with Databricks (non-negotiable)
- Strong expertise in:
- Python
- SQL
- Spark / distributed data processing
- Experience building end-to-end data platforms in AWS
- Proven implementation of medallion architecture / lakehouse design
Integration & Complexity Experience
- Experience integrating multiple ERP systems or fragmented environments
- Background in M&A-heavy or decentralized organizations is a strong plus
- Ability to operate in environments with little standardization and high ambiguity
Data Product Mindset
- Experience building data products, not just pipelines
- Ability to translate business needs into scalable data solutions
Leadership + Hands-On Balance
- Prior experience at Lead / Principal / Director level
- Comfortable being both architect and executor
- Proven ability to build from 0 ? 1
What Success Looks Like
In the first 6–12 months, you will:
- Stand up a scalable Databricks data foundation
- Begin consolidating data from dozens of siloed systems
- Deliver initial data products to the business
- Establish governance, standards, and engineering discipline
- Enable the first wave of AI-driven use cases
Why This Role is Compelling
- True greenfield build with executive support
- Direct impact on enterprise transformation + AI strategy
- High visibility across business and leadership
- Opportunity to shape long-term data and AI architecture
Context from Current State
- 50+ systems across acquired entities, many disconnected
- Databricks already in place and positioned as the future core platform
- Snowflake being deprecated for limited use cases
- Strong executive alignment around data + AI as strategic priorities
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