Director, Data Automation

We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: you'll actively leverage existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real. Introduction to role: Are you ready to build intelligent automation that makes trusted data instantly available for the decisions that change patient outcomes and accelerate our business? Do you see yourself leading a high-performing team to transform how data fuels analytics, AI and digital products across a global enterprise? As Director, Data Automation, you will lead a team of data engineers and automation specialists to design, deliver and scale modern data products and automated workflows. Your leadership will ensure our data is reliable, reusable and secure powering everything from research insights to operational excellence. You will partner with domain experts, product leaders and technologists to embed best-in-class engineering practices, orchestration and data quality into the backbone of our digital transformation. Accountabilities: - Leadership and Team Development: Lead, mentor and grow a team of data engineers and automation engineers; establish engineering standards and ways of working; manage priorities, capacity and delivery commitments; foster a culture of automation, continuous improvement and operational excellence; support recruitment, performance management, career development and succession planning. - Data Engineering: Design and oversee scalable data pipelines and data products; ensure reliable ingestion, transformation, integration and delivery of structured and unstructured data; drive reusable architectures, metadata and lineage capabilities; champion CI/CD, testing, observability and Infrastructure-as-Code; ensure performance, scalability, security and compliance are built in. - Data Automation: Identify and automate manual data processes and operational workflows; lead adoption of workflow orchestration, automation frameworks and self-service capabilities; develop automated monitoring, alerting, reconciliation and quality controls; improve efficiency through standardization and intelligent automation; prioritize automation opportunities with measurable business impact. - Data Quality, Governance and Compliance: Implement controls for data accuracy, completeness, consistency and traceability; align with enterprise data standards and policies; ensure appropriate controls for regulated and sensitive data; support audit readiness and compliance; promote FAIR and data stewardship principles where applicable. - Stakeholder Management: Collaborate with business functions, data product owners, analytics teams and enterprise technology; translate business requirements into scalable technical solutions; communicate progress, risks, dependencies and delivery outcomes to leadership; act as a trusted advisor on data engineering and automation capabilities. Essential Skills/Experience: Education - Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or related discipline. Experience - 8+ years of experience in data engineering, data platform development, or related disciplines. - 2+ years leading technical teams and delivering complex data initiatives. - Proven experience delivering enterprise-scale data platforms and automated data solutions. Technical Skills - Strong hands-on experience with Python and SQL. - Experience designing and building data pipelines and ETL/ELT processes. - Experience with cloud data platforms (AWS preferred). - Knowledge of orchestration frameworks (e.g., Airflow, Data Factory, Prefect). - Experience with Spark or distributed data processing technologies. - Experience with Spark, Snowflake, Databricks or distributed data processing technologies. - Understanding of data modelling, metadata, lineage, and data quality frameworks. - Familiarity with DevOps practices, CI/CD, Git, automated testing, and monitoring. - Experience with both structured and unstructured data. Leadership Competencies - Strategic thinking and problem solving. - People leadership and coaching. - Strong stakeholder engagement. - Delivery and execution focus. - Continuous improvement mindset. - Ability to influence across cross-functional teams. - Strong communication and collaboration skills. Desirable Skills/Experience: - Background in regulated industries and audit-ready data controls. - Experience implementing self-service data platforms and data product operating models. - Exposure to streaming data, event-driven architectures and real-time automation. - Experience partnering with data science and ML engineering teams to producti