Director of Data

ComPsych Corporation•,

1d•$225,000 - $250,000

About The Position

ComPsych® is the worldwide leader in organizational mental health, well-being, and absence management, dedicated to igniting human potential in workplaces across the globe. For over 40 years, we have combined the best in technology with unmatched human expertise to help individuals and their organizations thrive. Our GuidanceResources® and AbsenceResources® solutions deliver end-to-end mental health, well-being, work-life, health navigation, and absence support to more than 75,000 customers worldwide, touching more than 160 million lives across 200 countries. Visit compsych.com to find out why 40% of the Fortune 500 choose ComPsych for their mental health and absence management needs. We are seeking a Director of Data to lead our data organization through a significant transformation — modernizing our reporting infrastructure, building data science capability from the ground up, and establishing the 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'll inherit 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 that expertise in-house, retire the legacy system, and build a data science function that positions us to embed AI into our product.

Requirements

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

Nice To Haves

Familiarity with legacy enterprise reporting tools (e.g., Crystal Reports) and relational databases (e.g., Oracle) — enough to understand what you're migrating away from
Experience preparing data infrastructure to support machine learning or AI product features (feature stores, data labeling, MLOps foundations, etc.)
Background in a product-led or SaaS organization
Experience with data governance and privacy/compliance considerations relevant to HR and Healthcare

Responsibilities

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 — 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 for a modern data org, replacing ad hoc legacy practices
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 practices appropriate to a company relying more heavily on data for decision-making and product features
Build a data science function from scratch: define its charter, hire its first members, and establish how it collaborates with product, engineering, and analytics
Identify and 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 future AI/ML initiatives
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