- Develop and maintain comprehensive data architecture strategies tailored to the unique needs of Clinical and Operational data management.
- Design scalable, efficient, and secure databases, data warehouses, and data lakes to store and manage clinical data effectively.
- Define and implement data models, schemas, and integration frameworks to ensure the integrity and accessibility of clinical data.
- Lead all data engineering tasks and implement data pipelines, ETL processes to ingest, transform, and load clinical data from various sources into the data infrastructure.
- Optimize data workflows and performance through automation, parallel processing, and data partitioning techniques.
- Collaborate with data scientists and analysts to support advanced analytics, machine learning, and predictive modeling initiatives.
- Integrate disparate clinical systems, applications, and data sources to enable interoperability and data exchange across the life sciences ecosystem.
- Develop APIs, interfaces, and middleware solutions for seamless communication between clinical software systems and databases.
- Ensure compatibility and compliance with industry standards such as HL7, FHIR, and others.
- Implement security controls, encryption mechanisms, and access management policies to protect sensitive data from unauthorized access, breaches, and cyber threats.
- Monitor compliance with healthcare regulations such as HIPAA, GDPR, and other data privacy laws, and implement measures to address potential risks and vulnerabilities.
- Conduct performance tuning and optimization of databases, queries, and data processing pipelines to enhance efficiency, reliability, and scalability.
- Monitor system health, data integrity, and performance metrics using monitoring tools and implement proactive measures to address issues and bottlenecks.
- Document data architecture designs, technical specifications, and operational procedures to facilitate knowledge transfer and support ongoing maintenance and enhancements.
- Provide guidance, training, and mentorship to team members and stakeholders on best practices in data management, architecture, and engineering.
- Work closely with cross-functional teams including statisticians, statistical programmers, researchers, DigitalX members, and regulatory experts to understand requirements and priorities for clinical data management and analysis.
- Communicate effectively with stakeholders to ensure alignment of data architecture and engineering solutions with organizational goals and objectives.
- Stay abreast of emerging technologies, trends, and best practices in clinical data management, architecture, and engineering.
- Identify opportunities for process improvement, automation, and innovation to enhance the efficiency and effectiveness of data management practices. (変更の範囲) 会社内での全ての業務 【組織 / Organizational Context】
- Reports to Head of Foundational Data & Analytics
- Works very closely with the Data & Analytics teams in ensuring overall architecture alignment of Data & Analytics platforms.
- Communicate regularly with peers to update progress, discuss concerns, priorities, and projects.
- Regular contact with subordinates to mentor them and their performance.
- Supports team members in the interactions with senior business leaders to understand their longer-term needs, responding with architectures and plans, and providing expert consultancy.
- Works with DigitalX Business Partners to Influence business leaders and business process owners to maintain consistency with Data architecture roadmap for their area.
- Close collaboration with DigitalX Architecture & Technology teams.
- Close collaboration with DigitalX Risk & Compliance to ensure the Platforms are fully compliant.
- Communicate regularly with industry groups and suppliers.
- Collaborate with external service provider account managers and senior SMEs. 【Other】
- Assist with the management of a portfolio of 10+ toolsets and platforms 【応募要件 / Qualifications】
- Expertise in database design, data modeling, and data integration techniques.
- Proficiency in programming languages commonly used in data management and analysis, such as SQL, SAS, Python, or R.
- Expertise in working with databases and data warehousing technologies like SQL Server, Oracle, MySQL, AWS Redshift, Azure Synapse, Google BigQuery etc.
- Strong command in ETL and Data Integration tools like Talend, AWS Glue and DataBricks.
- Experience with Master Data Management (MDM) tools like Veeva Network, Reltio and IBM Infosphere
- Experience with BI tools like QlikSense, Tableau and PowerBI.
- In-depth understanding of life sciences business processes, adept at translating business requirements into effective technical solutions.
- Innovative problem-solving abilities for addressing complex data-related challenges.
- Experience with Agile methodology and mindset.
- Excellent communication and interpersonal skills, enabling effective collaboration with cross-functional teams, business stakeholders, and technical experts.
- Project management capabilities, ensuring adherence to timelines for successful solution delivery.
- Demonstrated leadership skills, including guiding technical teams, offering mentorship, and influencing architectural decisions.
- Demonstrated commitment to staying current with the latest trends, technologies, and best practices in the data and analytics field.
- Relevant certifications in cloud computing and data analytics tools/platforms are advantageous.
- Bachelor of Science degree in Computer Science, Information Systems, Data Science, or a related field.
- 10+ years of relevant experience working in in data architecture, engineering roles or related roles within a healthcare industry.
- 7+ years experience in Life Sciences industry
- Master of Science degree in Computer Science, Information Systems, Data Science, or a related field.
- Advanced Analytics experience
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