Associate Director, Global Data Engineering

Eisai•Nutley, NJ

1d•Hybrid

About The Position

The Associate Director, Global Data Engineering is a strategic and hands-on technology leader within Eisai's Global Data & Analytics (GDAS) organization. Reporting directly to the Global Data & Analytics Technology Lead, this role is responsible for architecting, delivering, and operationalizing scalable data, analytics, and AI platforms that support Eisai's global business objectives across Commercial, R&D, and Corporate functions. This position plays a critical leadership role in implementing the defined enterprise data strategy, modern data architecture, cloud platforms, and AI enablement capabilities that power data-driven decision making and innovation across Eisai. The Associate Director partners closely with business stakeholders, GDBT leaders, technology vendors, managed service providers, and global delivery teams to develop future-state data and analytics capabilities that are secure, compliant, flexible, and scalable. The role combines strategic technology leadership with hands-on architecture and engineering expertise across cloud platforms, modern data ecosystems, artificial intelligence, machine learning, and enterprise analytics. The successful candidate will drive the adoption of modern data engineering practices, governed data democratization, and AI-enabled solutions while ensuring alignment with Eisai's global architecture principles and business priorities. The Associate Director serves as a trusted advisor and technical leader, influencing strategic decisions and leading cross-functional teams spanning North America, EMEA, and Japan. Deep expertise in Databricks, Informatica, AWS, enterprise data architecture, and AI platform implementation is required.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related discipline required.
10+ years of experience designing, building, and supporting enterprise data platforms and data engineering solutions.
8+ years of experience implementing cloud-based data and analytics solutions using Amazon Web Services (AWS).
5+ years of experience leading technical teams and large-scale enterprise data initiatives.
Demonstrated experience leading geographically distributed teams and global technology programs.
Deep expertise with AWS data and analytics services including Databricks, S3, Athena, Glue, EMR, Lambda, RDS, EC2, DynamoDB, Redshift, and Kinesis.
Extensive experience implementing modern Lakehouse, Data Warehouse, Data Lake, and Data Mesh architectures.
Strong understanding of data integration patterns, ETL/ELT frameworks, streaming architectures, event-driven design, and distributed computing.
Deep expertise with the Databricks Data Intelligence Platform, including: Databricks Lakehouse Architecture, Unity Catalog, Delta Lake, Databricks Workflows, Databricks SQL, Apache Spark.
Experience supporting AI and machine learning platforms including: Generative AI solutions, Retrieval-Augmented Generation (RAG), Vector search and embeddings, AI governance and responsible AI practices, Data preparation and feature engineering.
Strong experience with Informatica IDMC and enterprise data integration platforms.
Advanced knowledge of data modeling, master data management, metadata management, data quality, and data governance principles.
Deep understanding of Data Vault, dimensional modeling, normalization, denormalization, graph, vector, and analytical data structures.
Hands-on experience with business intelligence and visualization tools, including Tableau and Power BI.
Strong software engineering skills utilizing SQL, Python, Scala, Java, and related open-source frameworks.
Experience with Apache Spark, Airflow, CI/CD pipelines, Git-based development practices, and enterprise application integration patterns.
Demonstrated ability to lead large-scale transformational initiatives and drive organizational adoption of new technologies.
Strong executive presence and ability to influence stakeholders at all organizational levels.
Proven ability to build consensus across business and technology organizations.
Ability to lead through both direct reporting relationships and matrixed organizational structures.
Strong written, verbal, and presentation skills.
Strong analytical and problem-solving capabilities.
Ability to translate complex technical concepts into business value and executive-level messaging.
Proven ability to prioritize effectively and deliver results in a fast-paced, global environment.
Familiarity with SDLC, Agile, ITIL, Enterprise Architecture, and IT Service Management practices.
Experience supporting systems subject to GxP, Computer System Validation (CSV), and 21 CFR Part 11 regulatory requirements.

Nice To Haves

Master's degree preferred.
Equivalent combination of education and relevant experience will be considered.
Experience within the pharmaceutical, biotechnology, healthcare, or regulated industries preferred.
Knowledge of pharmaceutical business processes, clinical development, commercial operations, and research environments preferred.

Responsibilities

Inspires, leads, and directs global data engineering teams to advance the adoption and effective use of enterprise data, analytics, and AI capabilities.
Partners with business and technology leaders to define the strategic roadmap for data engineering, analytics, and AI platforms supporting Eisai's global business objectives.
Contributes to the overall Data & Analytics strategy while owning technology enablement plans, implementation roadmaps, and associated budget planning.
Leads the development of future-state enterprise architecture patterns for data ingestion, integration, storage, governance, analytics, AI, and consumption.
Designs, architects, and implements enterprise-scale cloud data platforms supporting advanced analytics, data science, reporting, and AI use cases.
Develops and maintains architectural standards, reference architectures, and engineering best practices across data, analytics, and AI ecosystems.
Leads the design and implementation of data ingestion, transformation, storage, virtualization, and consumption frameworks supporting next-generation data products.
Enables governed self-service analytics and data democratization capabilities while maintaining enterprise security, compliance, and governance standards.
Evaluates emerging technologies and industry trends, recommending innovative capabilities that create business value and improve operational efficiency.
Provides technical leadership for modern AI, machine learning, and GenAI initiatives across Eisai's data ecosystem.
Leads architecture and implementation efforts utilizing the Databricks Data Intelligence Platform, including Lakehouse architecture, Delta Lake, Unity Catalog, workflows, data governance, and AI/ML capabilities.
Supports enterprise AI initiatives through scalable data preparation, feature engineering, model operationalization, vector search, retrieval-augmented generation (RAG), and AI governance best practices.
Works with, and leads as needed, high-performing global teams of data engineers, architects, analysts, and technical consultants.
Coaches and mentors technical teams on architecture, engineering disciplines, cloud technologies, and operational excellence.
Fosters a culture of continuous learning, collaboration, accountability, innovation, and customer focus.
Influences global cross-functional teams and stakeholders to achieve strategic outcomes through collaboration and shared ownership.
Collaborates with internal stakeholders, consulting partners, technology vendors, and managed service providers to successfully deliver complex global initiatives.
Presents technical strategy, architecture decisions, and project progress to leadership and executive stakeholders.
Ensures technology solutions align with business priorities while balancing scalability, performance, security, maintainability, and cost optimization.
Embodies and consistently demonstrates Eisai Values by challenging the impossible through innovation and curiosity, taking ownership and accountability for outcomes, treating others with dignity and mutual respect, and doing the right thing through integrity, transparency, fairness, and compliance.
Demonstrates ONE Team Behaviors by collaborating across functions, driving results with urgency and resilience, developing talent, and helping shape the future in support of Eisai's hhc mission and strategic priorities.