Data Architecture, Associate Director

Job description

Job Description The Associate Director leads and develops a programming and reporting team - set goals, assign work, coach performance, and manage recruiting/onboarding - while communicating status and risks to leadership and partners. Provide hands-on technical review, solutioning support, enforce SOPs/standards, manage workload and prioritization, track quality and timelines, and drive best practices (code review, reusable components, test automation) and continuous improvement. Responsibilities Programming and reporting • Lead design and deployment of clinical technology system solutions (e.g., for EDC, RTSM, and eCOA/ePRO) using programming frameworks and automation tools. • Provide technical oversight for clinical programming, reporting, and data integration across portfolios. • Recommend and implement tools to streamline design, build, and validation processes. • Apply data literacy to design transformation strategies for actionable insights. • Develop advanced reporting solutions (dashboards, listings, visual analytics) with reusable components and role-based access. • Data Engineering • Define and govern integration architecture, including data sources and transformation workflows. • Ensure consistent implementation of enterprise standards and reusable assets. • Monitor and troubleshoot data ingestion and consumption for reliability. • Automate and strengthen data engineering processes to reduce risk and improve efficiency. • Develop robust data models, semantic layers, and curated datasets; enforce quality checks. Process • Drive process optimization by identifying gaps and implementing improvements. • Translate strategy into clear priorities, roadmaps, and ways of working for assigned domains. • Lead testing strategies for solutions; automate validation and ensure traceability. • Contribute to resource planning and workload distribution across global teams. • Set documentation and audit standards; ensure compliance through rigorous change management. • Lead cross-functional collaboration, meetings, and enterprise-level improvement programs. • Influence adoption of data standards, tools, and automation for better delivery and decision-making. • Provide leadership, coaching, and mentoring to build capabilities and foster a culture of quality and collaboration. • Support release management across environments; align stakeholders, lead UAT, and improve reporting standards. • Partner across teams to turn data and technical findings into clear, actionable recommendations • Act as a reliable partner to GDMS and other cross-functional teams, actively seeking input, aligning on priorities, and closing feedback loops to drive high-quality, coordinated delivery. People management • Set clear objectives aligned to organizational goals; assign work and set priorities. • Conduct regular check-ins and annual reviews; coach for performance; provide recognition. • Help develop career plans; create growth opportunities and promotion cases; ensure appropriate training and mentoring. • Support recruiting and hiring; manage sensitive employee-relations matters (including separations) in partnership with HR. • Balance workloads to support value-added work and work–life sustainability; anticipate obstacles and adjust plans. • Coordinate contingent resources across geographies; ensure role clarity and effective handoffs. • Support management of an operating budget and optimize spend against priorities. • Align teams around a clear direction; facilitate team/functional meetings. • Embrace Enterprise Leadership Skills principles and serve as a role model to their team • Drive enterprise leadership skills in the team • Champions organizational change; drives adoption of new operating models and digital capabilities across global functions • Support staff in the resolution of operational challenges through direct engagement, facilitation, mentoring, and strong problem-solving techniques. Technical Skills • Expert-level proficiency in different technology languages (e.g., SQL, Python, SAS, and R) for implementing clinical data collectors, integrations, transformations, and visualizations • Evidence of experience in architecting and interoperability of EDC platforms, data integration environments, clinical operations systems, and cloud computing platforms • Proficiency with key data-management and/or clinical operations tools and platforms (e.g., systems for data capture, review, visualization, reconciliation, and reporting), with the ability to help select, configure, or optimize solutions. • Broad understanding of the data-management technology ecosystem (e.g., data capture, review, reconciliation, reporting, analytics, and enabling tools) and how components fit together across the end-to-end process. • Experience leveraging automation, scripting, or digital solutions to streamline data-management activities and reduce manual effort. • Ability to interpret operational and quality metrics, use analytical/forecasting tools for capacity and scenario planning, and translate insights into clear decisions and actions. • Strong understanding of common clinical and regulatory data standards, clinical operational data models, metadata management, and controlled terminologies (e.g., MedDRA, WHODrug) to ensure consistency and submission readiness. • Strong understanding of validation, system lifecycle, data privacy, and System Development Lifecycle Management activities • Strong understanding of drug discovery process, FDA regulations, GxP / ICH guidelines • Ability to connect business outcomes to technical deliverables Soft Skills • Strong ability to lead teams in a matrixed, global organization while ensuring delivery excellence through effective problem-solving techniques • Demonstrated success in coaching, developing, and performance-managing high-performing individuals • Builds strong partnerships across technical, business, and quality functions to enhance collaboration and deliver integrated outcomes • Balanc