Sr Director, Enterprise Data & Analytics

Tarsus Pharmaceuticals•Irvine, CA

13h•Hybrid

About The Position

We are seeking a visionary and results-driven Senior Director of Enterprise Data & Analytics to serve as a strategic leader and key partner to the business. This senior leadership level role will be responsible for expanding and executing the company's enterprise data strategy, analytics capabilities, and driving the adoption of advanced AI and machine learning solutions across commercial and enterprise functions. The ideal candidate brings deep pharmaceutical and life sciences expertise, hands-on experience with modern cloud data platforms, and the strategic mindset to build world-class data capabilities that enable faster, smarter decision-making across the enterprise.

Requirements

Bachelor’s in computer science, Information systems, Engineering or related field, advanced degrees such as MBA or MS will be a plus.
15+ years of progressive experience in data, analytics, and technology leadership, with a minimum of 5 years in a senior leadership role preferably in a life sciences.
Deep pharmaceutical or life sciences industry experience and business acumen with comprehensive understanding of commercial data ecosystems including HCP data, claims data, specialty pharmacy, market access, and patient services from leading data sources and partners.
Familiarity with regulatory and compliance requirements relevant to pharmaceutical data (e.g., HIPAA, GDPR, 21 CFR Part 11).
Proven track record of building and scaling enterprise data platforms in a cloud environment, with deep technical fluency in data management tools such as Databricks, Snowflake, Microsoft Azure, and AWS and data visualization tools such as Tableau, PowerBI and Spotfire.
Experience integrating life sciences CRM and commercial applications — such as Veeva CRM, Veeva Vault, Salesforce, and Salesforce Marketing Cloud — with enterprise data platforms.
Proven experience driving the implementation and adoption of Generative AI, predictive modeling, and machine learning capabilities within enterprise systems and data platforms.
Exceptional executive communication and storytelling skills with the ability to present complex data strategies to non-technical senior leaders and board-level audiences.
Strong financial acumen with experience managing budgets and spending for all data analytics related projects and consultants.
Good project management experience to manage large projects in an agile or waterfall framework depending on the type and complexity of the project.
A good team player with experience in managing and developing diverse, distributed teams of data professionals.

Nice To Haves

Empowering Others - Fosters empowerment by aligning authority with accountability, developing leaders’ decision-making capability, and creating systems that support performance and growth.
Emotional Intelligence - Foster trust and psychological safety, navigating complex interpersonal dynamics with compassion and accountability, and adapting leadership style to support others while maintaining composure under pressure.
Grows Capacity - Builds organizational capacity by developing talent systems, coaching cultures, and strategic partnerships that grow leadership strength and prepare the next generation of leaders.
Business Acumen - Demonstrates strong business acumen by anticipating market dynamics and using financial and strategic insight to guide investments, manage risk, and align priorities with long-term organizational value.
Innovative Mindset and Action - Demonstrates an innovative mindset by championing new ideas, investing in enabling systems and partnerships, and translating innovation into sustainable growth and organizational resilience.

Responsibilities

Define and own the multi-year enterprise data and analytics strategy, and roadmap aligning closely with the company’s commercial and corporate priorities ensuring data capabilities as a competitive differentiator.
Serve as a trusted advisor and strategic partner to senior leadership and business stakeholders across commercial, finance, HR, medical affairs, market access, R&D and operations — translating complex data opportunities into clear business value.
Partner with senior leadership team and IT to develop and execute corporate AI strategy and adoption
Proactively understand the industry trends and bring innovative data and AI capabilities to improve AI/ML adoption including Gen AI, integration of AI applications through MCP, predictive modeling and advanced analytics that drive measurable business outcomes.
Lead the architecture, evolution, scalability, and lifecycle of a modern, cloud-native enterprise data platform (e.g., Databricks, Azure, Tableau), ensuring it robustly supports the organization’s advancing analytics and AI workloads.
Ensure robust data governance, security, privacy, retention and compliance standards — working in close partnership with Information Security, Legal, and Privacy teams to safeguard all data assets in alignment with HIPAA, GDPR, and other applicable regulations.
Direct the strategy and governance for onboarding complex life sciences data ecosystems—including commercial, claims, provider (HCP), and third-party logistics (3PL) streams—into a unified data landscape.
Establish the architectural strategy for integrating advanced AI capabilities and external applications (e.g., Veeva, Salesforce) using modern, agnostic data exposure frameworks like MCP to drive seamless interoperability.
Provide strategic oversight for the engineering teams responsible for building and maintaining robust ETL/ELT pipelines across commercial and enterprise data ecosystems.
Serve as the organizational authority and subject matter expert on enterprise data architecture, data integration, and business intelligence—ensuring delivery of high-impact executive insights and robust self-service reporting frameworks.
Implement data quality monitoring frameworks and SLAs to ensure that business-critical data assets meet accuracy, completeness, and timeliness standards.
Lead strategic vendor relationships across data platform providers (e.g., Snowflake, Databricks), pharma data suppliers (e.g., IQVIA), analytics tools vendors, and implementation partners.
Lead and manage IT budgets for all enterprise data and analytics spend.
Champion a data-driven culture across the organization by establishing shared data literacy programs, self-service analytics frameworks, and executive-level reporting capabilities.
Develop and retain a high performing team of data engineers, analysts, developers and consultants, fostering a culture of innovation, continuous learning and technical excellence.