We are seeking aDirector of Datato lead our data organization through a significant transformation 1 modernizing our reporting infrastructure, building data science capability from the ground up, andestablishingthe data foundation needed to power AI capabilities in our product.

This is a hands-on leadership role for someone who can operate at two levels simultaneously: setting a multi-year data strategy while also rolling up their sleeves to assess technical debt, guide a team through a skills transition, and make hard calls about people and technology.You'llinherit a team currently running on legacy tools (Crystal Reports, Oracle) that is in the middle of a migration to a modern cloud stack (Databricks, Power BI), currently supported by contractors. Your mandate is to bring thatexpertisein-house,retirethe legacy system, and build a data science function that positions us to embed AI into our product.

Team leadership & talent strategy

• Lead and grow a team of reporting and data engineers, and stand up a new data science function within the org

• Make and own decisions about team composition 1 hiring new talent, upskilling existing team members, and restructuring roles that are no longer aligned with the team's direction

• Recruit and onboard data engineers, analytics engineers, and data scientists as the function scales

• Build a team culture and set of practices (code review, documentation,on-call, etc.)appropriate fora modern data org, replacing ad hoc legacy practices

Technology modernization

• Own the transition off Crystal Reports and Oracle onto Databricks and Power BI, including setting a realistic deprecation timeline for legacy systems

• Partner with and eventually reduce reliance on external contractors by building durable in-house capability

• Define architecture, data modeling, and engineering standards for the new platform

• Establish data governance, quality, and observability practicesappropriate toa company relying more heavily on data for decision-making and product features

Data science & AI enablement

• Build a data science function from scratch: define its charter, hire its first members, andestablishhow it collaborates with product, engineering, and analytics

• Identifyand prioritize the data capture, pipelines, and infrastructure needed to eventually support AI/ML features in the product

• Partner closely with product and engineering leadership to translate product AI ambitions into concrete data requirements

• Establish practices for data quality, labeling, and accessibility that will make data usable for futureAI/ML initiatives

Strategy & stakeholder management

• Develop and communicate a multi-year data roadmap, including migration milestones, team growth plans, and investment asks

• Serve as the primary point of contact for data strategy with senior leadership, translating business needs into technical priorities and vice versa

• Manage budget and vendor/contractor relationships during the transition period

• Report on progress, risks, and trade-offs as the team transitions off legacy systems

• 8+ years in data engineering, analytics engineering, or data leadership roles, including 3+ years managing teams

• Proven experience leading a legacy-to-modern data platform migration (e.g., moving off on-prem/legacy BI tools to a cloud data platform)

• Direct experience with Databricks and Power BI (or comparable modern cloud data/BI stack) in a hands-on or architectural capacity

• Experience building or scaling a data science or analytics function, including hiring the first members of a team

• Strong understanding of data architecture, data modeling, and data governance fundamentals

• Experience managing external contractors/vendors and transitioning work in-house

• Excellent communication skills; comfortable presenting data strategy and trade-offs to senior/executive stakeholders

Preferred

• Familiarity with legacy enterprise reporting tools (e.g., Crystal Reports) and relational databases (e.g., Oracle) 1 enough to understand whatyou'remigrating away from

• Experience preparing data infrastructure to support machine learning or AI product features (feature stores, data labeling,MLOpsfoundations, etc.)

• Background in a product-led or SaaS organization

• Experience with data governance and privacy/compliance considerations relevant to HR and Healthcare

Success in This Role Looks Like

• A clear, communicated plan (with milestones) for retiring the legacy reporting system

• A right-sized, upskilled teamoperatingconfidently on the new stack, with reduced dependency on contractors

• A functioning data science team with a clear charter and early wins

• A data foundation (pipelines, quality, accessibility) that product and engineering can build AI features on top of

• Trust from senior leadership as the go-to voice on data strategy

• Full benefits package, including Paid Time Off (PTO), medical, dental, vision, 401(k) with match, robust EAP, wellness program, and much more
• The salary range for this position is $225,000 - $250,000 (USD). The base salary range represents the anticipated low end and high end of the range for this position. The actual compensation will be influenced by a wide range of factors including, but not limited to previous experience, education, pay market/geography, and scheduled hours.