Associate Director, Data and Analytics

Role Summary

Associate Director, Data and Analytics will play a critical leadership role within the Data & Analytics organization, supporting Corporate, Finance, and Supply Chain functions. The role is responsible for translating complex business requirements into scalable analytics, predictive, and conversational analytics solutions by leveraging deep domain expertise and modern data technologies. The Associate Director will oversee solution architecture, data quality, advanced analytics development, and cross-functional collaboration to ensure high-impact, trusted, and transparent insights for the business.

Responsibilities

• Technical Leadership and Strategy: Provide technical leadership in the development and implementation of Supply Chain, Finance and corporate function analytics solutions, aligning with business objectives and industry best practices.
• Execute Madrigal’s established enterprise data strategy, ensuring alignment with corporate, supply chain, and finance priorities and accelerating analytics delivery.
• Champion data governance, trust, and transparency by leveraging Alation for data cataloging, lineage, metadata management, and access control.
• Analytics Solution Architecture & Design: Architect scalable data pipelines and analytics platforms using Azure and Microsoft Fabric, enabling rapid insights and efficient data processing.
• Design and maintain semantic data models and dbt transformations to create well-governed, reusable, and trusted analytics layers.
• Build advanced Power BI dashboards, semantic models, dataflows, and Fabric-based analytics workflows to support enterprise and self-service reporting.
• Integrate Workday, Coupa, NetSuite, and other enterprise systems into unified, high-quality data models supporting corporate, finance, and supply chain analytics needs.
• Advanced Analytics, Predictive & Conversational Solutions: Lead the development of predictive models, optimization analytics workflows to support forecasting, financial planning, and supply chain optimization.
• Apply statistical modeling and advanced analytics to extract strategic insights from complex datasets.
• Deliver conversational analytics solutions to support self-service and intuitive data access.
• Data Quality, Automation, Privacy & Trust: Develop and automate data quality rules, profiling, and anomaly detection to ensure accuracy, completeness, and consistency of analytics outputs.
• Implement data privacy and policy enforcement workflows using Immuta, ensuring secure, compliant, and governed access to sensitive datasets in partner with data owners/stewards
• Drive enterprise-wide trust by establishing transparent data quality metrics, automated validation layers, and auditable pipelines inside Fabric, dbt, and Azure.
• Cross-Functional Collaboration & Delivery Execution: Collaborate with business stakeholders, data engineers, data scientists, and system owners to translate business requirements into technically sound analytics solutions.
• Act as a senior technical partner to business leaders, ensuring analytics solutions meet strategic and operational needs.
• Lead Agile execution through JIRA for sprint management and Confluence for documentation, standards, and process governance.
• Mentor junior analysts and engineers to build technical excellence and cross-functional capabilities.
• Continuous Improvement, Innovation & Enablement: Evaluate emerging tools and technologies across analytics engineering, data governance, data quality, and conversational analytics to enhance enterprise capabilities.
• Drive adoption of modern self-service analytics capabilities through semantic modeling, cataloging (Alation), and governed data access (Immuta).
• Contribute to reusable frameworks, best practices, documentation, and governance processes that improve analytics efficiency and ensure data trustworthiness.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field; PhD preferred.
• 10+ years of experience in analytics engineering, data engineering, or advanced analytics roles, preferably in the pharmaceutical or life sciences industry.
• Strong proficiency in Python and R, with demonstrated experience in statistical modeling, and analytical computing.
• 8+ years of experience in data manipulation, integration, SQL development, and building scalable data products.
• Proven expertise with visualization and analytics platforms such as Power BI, Tableau, and enterprise BI ecosystems.
• Strong hands-on experience with Microsoft Fabric, including Power BI semantic models, dataflows, pipelines, and workspace governance.
• Deep expertise with dbt for modeling semantic layers and building scalable, modular, production-ready transformations.
• Experience designing and implementing automated data quality rules, profiling, anomaly detection, and validation frameworks.
• Proficiency with Alation for data cataloging, metadata management, lineage, stewardship, and access control.
• Experience working in Agile environments with JIRA and Confluence for project planning, sprint execution, and documentation.
• Strong leadership, communication, and stakeholder-management skills with the ability to influence technical and business teams and drive strategic outcomes.

Skills

• Strategic Thinking: Ability to translate business priorities into an actionable analytics strategy.
• Analytical Excellence: Demonstrates strong quantitative skills and ensures rigor, transparency, and clarity in insights.
• Influence & Communication: Communicates complex concepts simply, shapes decisions, and engages senior leadership effectively.
• Collaboration: Works effectively across functions and builds strong partnerships.
• Innovation & Continuous Improvement: Drives modernization, automation, and adoption of new technologies.
• Results Orientation: Delivers high-quality work, manages competing priorities, and operates with a bias toward action.