Job Description
The Associate Director, Data Architect (M-track) 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 [Electronic Data Capture], RTSM [Randomization and Trial Supply Management], and eCOA/ePRO [electronic Clinical Outcomes Assessment/ electronic Patient-Reported Outcomes]) 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 general 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.
People management
Align teams around a clear direction; set clear objectives aligned to organizational goals; assign work and set priorities accounting for work-life balance sustainability.
Conduct regular check-ins and annual reviews; coach for performance; provide recognition.
Develop career plans; create growth opportunities and promotion cases; ensure appropriate training and mentoring.
Lead recruiting and hiring and oversee performance management activities, including management of sensitive employee‐relations matters in partnership with HR.




Coordinate on‐shore/off‐shore and contingent resources; ensure role clarity and effective handoffs.
Manage an operating budget and optimize spend against priorities.
Inspires and ensures that team leaders are effectively supporting and empowering their individual leaders.
Technical skills
Expert-level proficiency in different technology languages (e.g., SQL, Python, SAS, and R) for implementing clinical data collectors, integrations, transformations, 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, WH
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📌 Associate Director, Data Architect, Gdms Data Integration & Automation (Buenos Aires)
🏢 PVH (Tommy Hilfiger/Calvin Klein)
📍 Buenos Aires