**Data Foundation POD Captain, EnablementX** Do you want to be part of an inclusive team that works to develop innovative therapies for patients? Every day, we are driven to develop and deliver innovative and effective new medicines to patients and physicians. If you want to be part of this exciting work, you belong at Astellas! Astellas Pharma Inc. is a pharmaceutical company conducting business in more than 70 countries around the world. We are committed to turning innovative science into medical solutions that bring value and hope to patients and their families. Keeping our focus on addressing unmet medical needs and conducting our business with ethics and integrity enables us to improve the health of people throughout the world. For more information on Astellas, please visit our website at www.astellas.com . This position is based in Northbrook, Illinois. Remote work from certain states may be permitted in accordance with Astellas’ Responsible Flexibility Guidelines. Candidates interested in remote work are encouraged to apply. **Purpose and Scope:** The Data Foundation POD Captain, responsible for leading the Databricks platform at the enterprise level for Astellas, plays a crucial role in driving data innovation and excellence using agile methodologies. This position is dedicated to overseeing the strategic alignment and execution of the Databricks initiatives, ensuring the platform is optimally leveraged to support Astellas' data-driven goals. The captain will coordinate cross-functional teams, foster a culture of experimentation and ownership, and ensure seamless integration of the Databricks platform within the broader enterprise architecture. This role exists to enhance data capabilities, streamline processes, and deliver impactful results that align with Astellas' vision and strategic objectives. **Essential Job Responsibilities:** The Data Foundation POD Captain will be a strategic and technical leader, accountable for driving the successful implementation, scaling and continuous evolution of Astellas' enterprise Databricks platform within a Data Mesh operating model. This role blends deep technical expertise with enterprise level leadership to drive business value through data productization, platform enablement and cross-functional collaboration. I. Strategic Leadership & Vision (Accountability: Data Mesh & Platform Strategy) + Define and Champion Data Mesh Principles: Lead the adoption and evolution of Data Mesh principles across the organization, ensuring alignment with Astellas' overall data strategy and business priorities. + Databricks Platform Strategy: Develop and execute the long-term vision and roadmap for the enterprise Databricks platform, ensuring it robustly supports the Data Mesh architecture, data marketplace, and domain-specific data product development. + Technology & Tooling Alignment: Identify and integrate new technologies, tools, and methodologies that enhance the Databricks platform's capabilities within the Data Mesh paradigm (e.g., data cataloging, governance, orchestration tools). + Thought Leadership: Act as a subject matter expert and evangelist for Data Mesh and Databricks, educating stakeholders and promoting a data-driven culture across the organization.II. Platform & Enablement (Accountability: Reliable & Scalable Data Platform) + Databricks Platform Ownership: Oversee the architecture, design and operations of the enterprise Databricks platform, ensuring its scalability, security, performance, and cost-efficiency. + Platform Enablement for Domain Teams: Provide tooling, best practices, guidelines, and self-service capabilities to empower domain teams to independently build, manage, and expose data products on the Databricks platform. + Infrastructure-as-Code (IaC) & Automation: Drive the implementation of IaC for Databricks infrastructure and resources, ensuring automated provisioning, configuration, and consistent deployment across environments. + Monitoring, Alerting & Cost Optimization: Establish comprehensive robust monitoring and alerting frameworks for the Databricks platform. Drive proactive platform tuning and cost optimization strategies without compromising performance or reliability. III. Data Product & Data Marketplace (Accountability: Data Product Lifecycle & Marketplace Success) + Data Product Standards: Collaborate with domain teams to define standards and enforce patterns, templates and quality standards for reusable, interoperable data products. + Enterprise Data Marketplace: Lead the development and growth of the data marketplace, ensuring discoverability, usability and consumer-centric access to data products. + Lifecycle Management: Define governance processes across the data product lifecycle, from ideation and development to deployment, versioning, deprecation, and consumption; to ensure long-term sustainability and value enablement. + Cross-Domain Interoperability: Champion and enforce technical patterns and governance mechanisms support seamless data interoperability and consumption across different data domains.IV. Governance & Compliance (Accountability: Data Trust & Security) + Data Governance Integration: Work closely with data governance teams to embed governance policies, data quality standards, security controls (e.g., access control, encryption), and compliance requirements directly into the Databricks platform and data product development processes. + Security & Access Management: Implement and enforce robust security measures, access controls, and data privacy protocols within the Databricks environment, adhering to industry best practices and regulatory requirements. + Auditability & Lineage: Ensure the Databricks platform supports full data lineage and auditability for all data products, supporting both transparency and regulatory readiness. V. Team Leadership & Collaboration (Accountability: High-Performing POD & Cross-Functional Alignment) + POD Leadership & Mentorship: Lead, mentor, and develop a high-performing Data Foundation POD, fostering a culture of innovation, collaboration, and continuous improvement. + Cross-Functional Collaboration: Serve as the primary technical liaison between domain data teams, central platform teams, security, and governance teams to ensure seamless integration and consistent application of the Data Mesh principles and stakeholder alignment. + Stakeholder Management: Effectively communicate technical concepts and strategic direction clearly to both technical and non-technical stakeholders, influencing decision-making and driving consensus. + Agile & DevOps Practices: Champion and implement Agile and DevOps methodologies within the POD and promote their adoption across data development practices. VI. Hands-on Technical Expertise (Accountability: Technical Excellence & Problem Solving) + Databricks Expertise: Maintain deep, hands-on expertise with Databricks features and services (e.g., Delta Lake, Unity Catalog, Photon, Spark optimization, Databricks SQL, MLflow, Workflows). + Data Architecture & Modeling: Provide technical direction on data architecture, data modeling (dimensional, medallion, data vault), and data pipeline design patterns suitable within a Data Mesh context. + Performance Tuning & Optimization: Troubleshoot and optimize complex Databricks workloads, ensuring efficient resource utilization and high performance. + Prototyping & Innovation: Drive rapid experimentation and lead the development of proofs-of-concept and prototypes for new data capabilities or architectural patterns using Databricks. **Qualifications** **Required:** I. Education & Core Experience: + Bachelor's degree in Computer Science, Engineering, Information Systems, or a closely related quantitative field. + Minimum of 10 years of progressive experience in data engineering, data platform architecture, data solutions leadership, or a closely related technical field within a large-scale enterprise environment. + Minimum of 3+ years of direct, hands-on experience leading the design, implementation, and operationalization of Data Mesh architectures and principles. This must include practical experience establishing data domains, promoting data product ownership, and enabling independent data product development teams. + Minimum of 3+ years of expert-level, hands-on experience with the Databricks Lakehouse Platform. This includes deep proficiency with core components such as Delta Lake, Unity Catalog, Photon, Spark optimization techniques, Databricks SQL, Workflows, Jobs, and MLflow. + Proven experience in building, deploying, and operating enterprise-scale data platforms on at least one major cloud provider (e.g., AWS, Microsoft Azure, or Google Cloud Platform). II. Technical Expertise: + Deep and practical understanding of Data Mesh architectural patterns, including data as a product, decentralized data ownership, self-serve data platform, and federated computational governance. + Mastery of data modeling techniques suitable for lake house environments (e.g., Medallion Architecture, Kimball dimensional modeling, Data Vault principles). + Expertise in designing, building, and optimizing robust, scalable, and fault-tolerant data pipelines (ETL/ELT) using Databricks and cloud-native services. + Strong proficiency in at least one relevant programming language for data engineering (e.g., PySpark, Scala, Python, SQL). + Demonstrable experience with Infrastructure-as-Code (IaC) tools (e.g., Terraform, ARM templates, CloudFormation) for automating the deployment and management of Databricks workspaces and related cloud resources. + Solid understanding of data governance concepts (e.g., metadata management, data lineage, data cataloging, data quality frameworks) and their implementation within a Data Mesh / Databricks context. + Comprehensive knowledge of data security best practices for cloud data platforms, including access control (IAM, Unity Catalog), encryption at rest and in transit, and data privacy regulations. III. Leadership & Strategic Acumen: + Proven experience in leading, mentoring, and developing high-performing technical teams (e.g., data architects, data engineers, platform engineers). + Exceptional verbal and written communication skills, with the ability to clearly articulate complex technical concepts, strategic visions, and business value to diverse audiences, from technical practitioners to executive leadership. + Demonstrated ability to drive organizational change and influence key stakeholders without direct authority, fostering adoption of new methodologies and technologies. + Strong analytical, problem-solving, and critical thinking abilities, with a track record of successfully resolving complex technical challenges. + Experience in facilitating cross-functional collaboration between various data domains, central platform teams, governance bodies, and business units. **Preferred Qualifications:** + Master's degree or higher in Computer Science, Data Science, Engineering, or a related field. + Databricks Certified Professional certifications (e.g., Data Engineer Professional, Lakehouse Architect). + Experience with specific data cataloging and governance tools (e.g., Collibra, Alation, Purview, Atlan) and their integration with Databricks. + Familiarity with DevOps and MLOps practices in a data context, including CI/CD pipelines for data products and machine learning model deployment. + Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Spark Streaming, Databricks Structured Streaming). + Knowledge of data visualization tools (e.g., Tableau, Power BI, Looker) and how they connect to Databricks for data product consumption. + Prior experience in the pharmaceutical or life sciences industry, understanding relevant data privacy and regulatory compliance (e.g., GxP, HIPAA, GDPR). + Experience with cost optimization strategies for large-scale cloud data platforms. + Active participation in the Data Mesh or Databricks community (e.g., speaking engagements, open-source contributions, blog posts). **Working Environment:** At Astellas we recognize the importance of work/life balance, and we are proud to offer a hybrid working solution allowing time to connect with colleagues at the office with the flexibility to also work from home. We believe this will optimize the most productive work environment for all employees to succeed and deliver. Hybrid work from certain locations may be permitted in accordance with Astellas’ Responsible Flexibility Guidelines. **Benefits:** + Medical, Dental and Vision Insurance + Generous Paid Time Off options, including Vacation, Sick time, plus national holidays including Heritage Days, and Summer and Winter Breaks + 401(k) match and annual company contribution + Company paid life insurance + Annual Corporate Bonus and Quarterly Sales Incentive for eligible positions + Long Term Incentive Plan for eligible positions + Referral bonus program Category CDTO Office Astellas is committed to equality of opportunity in all aspects of employment. EOE including Disability/Protected Veterans