Director of Data Engineering

We’re partnered with a Tempe-based organization undertaking a major modernization of its enterprise data platform, with a central focus on Lakehouse architecture. This role will lead the strategy and execution of a Databricks-based Lakehouse implementation, serving as the backbone for analytics, reporting, and downstream AI initiatives.

This is a senior leadership role for someone who has been through a Lakehouse build before, understands what works, what breaks, and what needs to be governed early so it doesn’t turn into an expensive data swamp.

What You’ll Be Doing

Lakehouse Strategy & Implementation (Core Focus)

• Own the design and execution of a Lakehouse architecture, ideally on Databricks

• Lead platform decisions around ingestion, transformation, storage, and consumption layers

• Establish best practices for Delta Lake, data modeling, governance, and cost control

• Partner with analytics and data science teams to ensure the platform supports real workloads — not slide decks

Data Engineering Leadership

• Build, mentor, and scale a high-performing data engineering organization

• Set standards for code quality, reliability, observability, and delivery discipline

• Balance hands-on technical oversight with senior-level leadership and delegation

Enterprise Data Enablement

• Champion data governance, lineage, quality, and security as first-class concerns

• Act as a trusted advisor to senior leadership on data architecture and platform evolution

• Translate technical tradeoffs into clear business implications for non-technical stakeholders

Operational Excellence

• Ensure data pipelines meet expectations for reliability, scalability, and performance

• Drive best practices around orchestration, CI/CD, and monitoring

• Avoid both extremes: “move fast and break everything” and bureaucratic gridlock

Absolute Must-Haves

• Lakehouse experience: Direct involvement in a Lakehouse implementation, ideally using Databricks in production

• Senior data engineering leadership: 10–15+ years in data roles with meaningful team and platform ownership

• Enterprise mindset: Experience operating data platforms with governance, security, and real business accountability

Nice-to-Haves

• Azure-based data platforms

• Snowflake or hybrid Lakehouse / warehouse environments

• Unity Catalog, data lineage, or MDM tooling exposure

• Experience modernizing legacy data ecosystems into Lakehouse architectures

What This Role Is Not

• Not theoretical Lakehouse experience (“read the blog posts”)

• Not a hands-off manager detached from architecture decisions

• Not a pure greenfield startup — this is modernization with constraints

Why This Role

• Opportunity to shape and own a Lakehouse platform at the enterprise level

• Strong executive visibility and influence

• Backing to build the right platform — not just duct-tape the old one

Determining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to the individual’s skill sets, experience and training, licensure and certifications, office location and other geographic considerations, as well as other business and organizational needs. With that said, as required by local law in geographies that require salary range disclosure, Vaco/Highspring notes the salary range for the role is noted in this job posting. The individual may also be eligible for discretionary bonuses, and can participate in medical, dental, and vision benefits as well as the company’s 401(k) retirement plan. Additional disclaimer: Unless otherwise noted in the job description, the position Vaco/Highspring is filing for is occupied. Please note, however, that Vaco/Highspring is regularly asked to provide talent to other organizations. By submitting to this position, you are agreeing to be included in our talent pool for future hiring for similarly qualified positions. Submissions to this position are subject to the use of AI to perform preliminary candidate screenings, focused on ensuring minimum job requirements noted in the position are satisfied. Further assessment of candidates beyond this initial phase within Vaco/Highspring will be otherwise assessed by recruiters and hiring managers. Vaco/Highspring does not have knowledge of the tools used by its clients in making final hiring decisions and cannot opine on their use of AI products.