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 integral 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