Lead, Data Platforms, DD&T, Japan Corporate Function

Introduction of Takeda / タケダの紹介

タケダでは常に患者さんを中心に考え、世界中の人々により健やかで輝かしい未来をお届けすることを目指してきました。そして従業員一人ひとりにそれぞれの能力と熱意に応じた成長の機会を提供することにも組んで取り組んでいます。私たちと一緒に、世界中の人々のいのちに貢献し、さらなる成長と活躍を目指しませんか。

タケダは業界を牽引するグローバルリーダーです。従業員は四つの優先順位（患者さん中心、社会との信頼関係構築、レピュテーションの向上、事業の発展）とタケダイズム（誠実＝公正・正直・不屈）のもと一致団結しています。タケダイズムは私たちの信念であり正しい方向へ導く羅針盤です。私たちは日々の業務においてタケダイズムを体現しています。

Takeda is unwavering in our commitment to patients. With the patient at the center of everything we do, we continue to innovate and drive changes that will better their lives-we ’ re looking for like-minded professionals to join us.

Takeda is a global industry leader – we are united by our four priorities (Patients, Trust, Reputation, and Business) and our shared values of Takeda-ism: Integrity, Fairness, Honesty, and Person. Takeda-ism is more than just a word. It's a belief and a mindset which guides our decisions, behaviors, and interactions. It's how we drive to work and live, every day.

Lead, Data Platforms

The Opportunity

As a Data Platforms Leader, you will play a pivotal role in shaping Takeda's Data Platforms and Architecture vision and contributing to the company's strategy of becoming a Data-Driven Enterprise. You will work closely with business units and functions within Takeda’s Global Business and its data teams to strategically design data, processes, and technology to accelerate the delivery of life-saving products to the market. This ultimately enables Takeda to make better decisions that enhance the quality and efficiency of patient care. Your responsibilities will include developing data-driven solutions using current and next-generation technologies to meet evolving business needs. You will be expected to identify opportunities and propose potential technical solutions swiftly. Furthermore, you will design application systems that adhere to standard system development methodology and concepts for design, programming, backup, and recovery to deliver high-performance, reliable, and secure solutions.

As part of our transformational journey on Data & AI in Operations, we are taking the steps to advance to Data Mesh architecture. The current Datalake gives all Operations units access to critical data and analytic tools at pace, accelerating their work on life-saving medicines. The vision of EDS is also accelerating Operations’ data strategy of making our data Findable, Accessible, Interoperable, and reusable. This is achieved by creating a distributed data architecture and managing our data and data products, which will serve as a centerpiece of this strategy and the future evolution of Data Science.

Responsibilities

• Create best practices for the federated delivery teams building data solutions and products on Enterprise Data platforms that cater to batch, streaming, and real-time data.

• Working closely with Business Engagement leads and stakeholders at all levels through complex engagement models with the broader cloud ecosystem not limited but inclusive of AWS foundations for Infrastructure and data technologies, Databricks, Informatica, Kafka, Managed File Transfer, and 3rd party applications, ensuring they are excited by the Enterprise Data Services vision and solution strategy.

• In the first 30 – 90 days, study the current platform architecture and its dependencies on daily operations. Uncover pain points that can be prioritized with operations support. Advocate for continuous improvements.

• Collaboratively provide a roadmap for modernizing legacy capabilities inherent to the current platform. Support all data platform initiatives – Data Lake Strategy, Data Engineering and Platform development, Data Governance, Security Models, and Master Data Management.

• Establish a collaborative engineering culture based on trust, innovation, and a continuous improvement mindset. Utilize Industry best practices and agile methodologies to deliver solutions and extract efficiency through Continuous Development and Integration automation. Manage efforts to problem-solve engineering challenges and coordinate with project consultants and delivery/engagement managers.

• As a leading technical contributor who can consistently take a poorly defined business or technical problem, work it to a well-defined data problem/specification, and execute it at a high level, have a strong focus on metrics, both for their work's impact and its engineering and operations.

• Understanding the Data platform investments creates data tools for consuming services and uncovers opportunities for cost optimization. This assists the team in building and optimizing our platforms into an innovative unit within the company.

Skills and Qualifications

Qualifications & Experience:

• Education: Bachelor’s degree or higher in Computer Science, Information Technology, or equivalent work experience.

• Technical Expertise: Strong understanding of Technology and Solution Architecture with experience in designing scalable and cost-effective data solutions.

• Languages: Business-level Japanese speaking proficiency is required.

• Experience: Minimum 10+ years of relevant experience in data platforms, solutions, and delivery methodologies.

• Project & Risk Management:

  • Identify and escalate risks and issues within projects, ensuring proactive mitigation and resolution strategies.

  • Drive product strategy and prioritization aligned with IT architecture, deployment, and release management.

  • Evaluate business processes and integrate stakeholder perspectives to optimize workflows.

  • Guide teams in adopting product-centric approaches and digital dexterity.

  • Monitor portfolio progress, identify gaps, and provide strategic recommendations.

• Stakeholder & Communication Management:

  • Collaborate with business and technology leaders, internal/external partners, data governance teams, and security teams to ensure alignment with Enterprise priorities.

  • Excellent communication and relationship-building skills to engage with both technical and non-technical stakeholders.

  • Ability to lead by influence, ensuring smooth coordination across teams, departments, and external partners.

Core Technical Skills:

• Data Engineering & Cloud Expertise:

  • Big Data Workloads: Experience in scaling and optimizing large-scale data solutions for performance and cost-effectiveness.

  • Cloud Architecture: Expertise in designing data solutions on AWS (or equivalent cloud services) with best practices in security and networking.

  • ETL/ELT & Data Integration:

    • 5+ years in customer-facing technical roles with experience in ETL/ELT, Data Integration, Data Pipeline Orchestration, and Managed File Transfers (MFTs).

    • Hands-on experience with ETL/ELT/Orchestration tools (e.g., Informatica Data Management Cloud, Databricks, Tidal, Apache Airflow).

    • Experience working in distributed, big data environments.

  • SQL & Database Management:

    • Advanced working SQL knowledge and familiarity with relational and non-relational databases.

    • Expertise in building and optimizing big data pipelines, architectures, and datasets.

  • API, Messaging & Streaming:

    • Knowledge of API (Mulesoft), Messaging queue, pub/sub-stream processing, Streaming (Apache Kafka/Confluent Kafka)

  • DevOps & DataOps:

    • Hands-on experience with CI/CD, automation, infrastructure-as-code, and containerization.

  • Data Analytics & Root Cause Analysis:

    • Ability to analyze internal/external data and processes to drive business decisions and performance improvements.

Enterprise & Leadership Skills:

• Enterprise Data Environment:

  • Experience working in Enterprise Data Warehouses, Data Lakes (e.g., Databricks), Advanced Analytics, and Data Management.

  • Working experience with Data Quality, Data Privacy, Data Governance, Access and Identity (OKTA, SailPoint)

  • Working knowledge MFT solutions (e.g., Hulft, GlobalScape).

• Stakeholder Engagement:

  • Excellent communication and relationship-building skills to collaborate with cross-functional teams.

  • Ability to lead by influence and engage with technical and non-technical stakeholders.

• Data Platforms & Analytics:

  • Experience with Databricks Lakehouse (Delta Lake), Redshift, or equivalent data platforms.

  • Working knowledge of BI tools (PowerBI, Qlik, Tableau), REST API integrations, and SQL interfaces.

Nice-to-Have Technical Skills:

• Programming & Cloud Technologies:

  • Experience with Java, Python, Spark, Hadoop, Kafka, SQL, NoSQL, PostgreSQL, or other modern programming languages.

  • Familiarity with DevOps & Development Tools: JIRA, Git, Jenkins, Bitbucket, Confluence.

  • Understanding of failover, high availability, and scalability in public cloud environments (AWS, Azure).

  • Nice to have knowledge on Immuta