Lead Data Engineer
Newfire Global Partners
Salary undisclosed
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Description
Opportunity for impact
Newfire is seeking a Lead Data Engineer
What's the Project?
As the Data Engineer Lead, you will be the primary architect and technical visionary for our greenfield data warehouse implementation on Azure. You are responsible for designing the end-to-end modern analytics stack—from source system ingestion (Airbyte/Fivetran) to the final BI reporting layer. You will serve as the "face" of the data team, interfacing directly with the CEO and product owners to translate business needs into technical reality.
Key Responsibilities
- Architectural Design: Define target architecture and data models for a new Snowflake-based warehouse on Azure using Medallion Architecture principles.
- Tooling Selection & Strategy: Lead the evaluation and implementation of the semantic layer (e.g., Cube) and BI tools (e.g., Hex, Lightdash, or Metabase).
- Standards & Quality: Establish and enforce a rigorous Definition of Done (DoD) that includes documentation, testing, and peer review.
- Testing Strategy: Architect a proactive data quality framework using dbt tests and observability patterns to ensure a trustworthy EDW.
- Stakeholder Management: Interface with the CEO; manage expectations, clarify scope, and push back on unrealistic requirements while maintaining architectural soundness.
- Planning & Delivery Management: Own the data team's sprint planning, backlog grooming, and quarterly roadmap. Translate business priorities into a sequenced delivery plan; proactively surface risks and keep stakeholders aligned on scope, timeline, and trade-offs.
Skills, Knowledge and Expertise
- Cloud Infrastructure: Proven experience building and managing data platforms within the Azure ecosystem.
- End-to-End Stack Mastery: Experience designing and delivering a modern warehouse: Ingestion (Airbyte/Fivetran) → Snowflake → dbt → Semantic Layer/BI.
- Advanced Data Modeling: Deep expertise in Dimensional Modeling (Star Schemas), EDW principles, and Medallion Architecture.
- Quality Leadership: Experience implementing automated testing and data observability at scale; TDD experience is a significant bonus.
- Leadership Experience: Prior tenure as a Tech Lead, Data Architect, or Analytics Engineering Lead.
- Delivery & Roadmap Management: Demonstrated ability to own a technical roadmap end-to-end — breaking down a multi-month initiative into sprints, managing a backlog in a tool such as Jira, Linear, or similar, and communicating status and trade-offs clearly to non-technical executives. Experience working in an Agile/Scrum or iterative delivery cadence is required.
- Definition of Done: A disciplined approach; you do not consider a task "finished" until it is tested, documented, and validated.
- Resilience: Comfortable holding ground under scrutiny and direct feedback
- Outcome-Oriented: Cares deeply about the final analysis the business needs.
- Ownership: Taking full responsibility for the integrity and reliability of the platform so that stakeholders have complete trust in the data.
- As a Senior team member, you will be expected to actively participate in our hiring processes by serving on interview panels for future roles across the company
About this role
Newfire Global Partners is building a greenfield data warehouse on Azure, and they're looking for a Lead Data Engineer to own the entire technical vision end-to-end. You'd architect a modern analytics stack using Snowflake, dbt, and a semantic layer, then serve as the primary interface between the data team and executive leadership—including the CEO. This is a high-visibility role where you'll translate business priorities into a sequenced delivery roadmap, establish quality standards and testing frameworks, and make critical tooling decisions across ingestion, transformation, and BI layers.
The ideal candidate has deep hands-on experience building cloud data platforms in Azure, designing dimensional models and medallion architectures, and leading technical teams through multi-month initiatives in an agile cadence. You'll need proven success implementing automated data quality and observability at scale, managing backlogs in tools like Jira, and communicating trade-offs clearly to non-technical stakeholders. This role demands both architectural rigor and the resilience to push back on unrealistic scope while maintaining stakeholder trust.
This is a part-time, remote position based in Colorado at a fully funded, stable firm with a strong client base in healthcare technology and a track record across Fortune 500 and startup clients. You'd also participate in hiring for future roles across the company.
Pay for this role
The employer didn't post a pay range for this role. That usually means pay is set in negotiation, which favors whoever arrives with numbers. Check ranges on comparable Lead Data Engineer postings in your area, and analyze any offer before you accept it.
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