数据架构师负责人
Lead Data Architect
这不是一份职业,而是一份使命。
我们的员工是成功的基础。加入位于麦肯锡旗下Sarah Cannon Research Institute(SCRI)不断壮大的团队,你将有机会成为全球最大的基于社区的癌症项目之一,推动肿瘤治疗的发展,并改善全球癌症患者的结果。我们寻找有使命感的候选人,他们渴望推进对抗癌症的斗争,并每天为被诊断出癌症的患者带来改变。
我们的使命
患有癌症的人——那些努力预防、对抗和战胜癌症的人——是我们每个决策的核心。我们将最创新的医学人才与社区中最热情的护理人员结合在一起,正在改变医疗方式并实现个性化治疗。通过临床卓越和前沿研究,SCRI正在重新定义全球的癌症护理。
作为首席数据架构师,你将在推动我们所有产品中的数据库战略方面发挥关键作用。这个职位需要在数据架构方面有深厚的专业知识,以分析、设计和实施复杂的系统,确保稳健、可扩展的解决方案来支持我们的业务目标。你的专业知识将确保我们的数据基础设施稳健、可扩展,并与我们的使命保持一致,使我们能够利用数据的力量改善医疗交付,并支持我们对临床研究和患者的持续承诺。
岗位职责:
- 负责设计、构建和管理组织的数据基础设施。
- 制定数据收集、存储、处理和使用的方式蓝图,确保其可访问、可靠和安全。
- 设计允许组织有效管理和使用数据的结构和系统,确保数据成为决策和业务运营的宝贵资产。
- 创建并维护数据库架构、流程和标准的文档。
关键职责:
- 数据策略:制定并实施与业务目标一致的全面数据策略。这包括了解组织的数据需求,并制定有效的数据管理路线图。
- 数据建模:设计概念、逻辑和物理数据模型,以表示组织内部数据的结构和关系。
- 数据架构:创建并维护整体数据架构框架,包括数据
查看英文原文
It’s More Than a Career, It’s a Mission.
Our people are the foundation of our success. By joining our growing team at Sarah Cannon Research Institute (SCRI), a subsidiary of McKesson, you will have the opportunity to become part of one of the largest community-based cancer programs to advance oncology treatments and improve outcomes for cancer patients across the globe. We look for mission-driven candidates who have a desire to advance the fight against cancer and make a difference in the lives of patients diagnosed with cancer every day.
Our Mission
People who live with cancer – those who work to prevent it, fight it, and survive it – are at the heart of every decision we make. Bringing the most innovative medical minds together with the most passionate caregivers in their communities, we are transforming care and personalizing treatment. Through clinical excellence and cutting-edge research, SCRI is redefining cancer care around the world.
As a Lead Data Architect, you will play a pivotal role in driving our database strategy across all products. This role demands a profound expertise in data architecture to analyze, design, and implement complex systems ensuring robust, scalable solutions that support our business goals. Your expertise will ensure that our data infrastructure is robust, scalable, and aligned with our mission, enabling us to harness the power of data to improve healthcare delivery and support our ongoing commitment to clinical research and our patients.
Job Responsibilities:
- Responsible for designing, building, and managing the organization's data infrastructure.
- Create the blueprint for how data is collected, stored, processed, and used, ensuring it's accessible, reliable, and secure.
- Design the structure and systems that allow the organization to effectively manage and use its data, ensuring it is a valuable asset for decision-making and business operations.
- Create and maintain documentation for database architecture, procedures, and standards.
Key Responsibilities:
- Data Strategy: Develop and implement a comprehensive data strategy aligned with business goals. This involves understanding the organization's data needs and creating a roadmap for effective data management.
- Data Modeling: Design conceptual, logical, and physical data models that represent the structure and relationships of data within the organization.
- Data Architecture: Create and maintain the overall data architecture framework, including databases, data warehouses, data lakes, and other data systems.
- Data Mapping: Develop and implement data mapping rules to transform data from source systems to target systems, ensuring data accuracy and consistency.
- Data Integration: Design and implement processes for integrating data from various sources, ensuring data consistency and accuracy.
- Data Governance: Establish data governance policies and procedures to ensure data quality, security, and HIPPA compliance across all data systems and platforms.
- Technology Evaluation: Evaluate and recommend data management technologies and tools to support the organization's data needs.
- Problem Solving: Identify and resolve data-related issues, ensuring data integrity and reliability.
- AI Solutions: Design and implement architectures that seamlessly integrate AI models and algorithms with existing data infrastructures, including cloud-native and legacy systems.
- Collaboration: Work closely with stakeholders, including business analysts, data scientists, and IT professionals, to understand data requirements and translate them into technical solutions. Influence projects to make decisions related to data strategies including data quality, data architecture and data management best practices
Minimum Job Qualifications:
- Minimum of 7 years of experience in enterprise data architecture, including data requirements collection, data architecture analysis, evaluation, documentation, data modeling, design, development, model validation, and data integration in modern data platforms (e.g., Azure, Databricks, Snowflake).
- Bachelor’s Degree in Computer Science, Information Systems, Engineering, or equivalent experience.
Critical Skills:
- Minimum 10 years of experience in database engineering/management required.
- Knowledge of software development methodologies (e.g., Agile, DevOps, SDLC, CI/CD, GitHub).
- 7+ years' experience working with data sources (e.g. APIs) and databases such as Oracle, PostgreSQL, SQL Server, and cloud databases.
- Knowledge of cloud technologies like Azure (Data Factory, Databricks), AWS.
- Strong knowledge of industry best practices — code coverage.
- Strong knowledge of database concepts, data modeling techniques, system performance analysis and tuning, and data warehousing concepts.
- Knowledge of various operating systems such as Linux, Unix, and Windows.
- Ability to write complex queries and perform advanced database operations using SQL.
Preferred Skills:
- Expertise in modern cloud-native database solutions
- Experience with database migration tools and strategies, including handling zero-downtime migrations and data synchronization
- Proficiency in infrastructure-as-code and automation tools (Terraform) for database deployment and management.
- Ability to design scalable database architectures that support microservices and distributed systems
- Experience with various database patterns (CQRS, event sourcing, sharding strategies)
- Understanding of data modeling for both relational and NoSQL databases
About Sarah Cannon Research Institute
Sarah Cannon Research Institute (SCRI) is one of the world’s leading oncology research organizations conducting community-based clinical trials. Focused on advancing therapies for patients over the last three decades, SCRI is a leader in drug development. In 2022, SCRI formed a joint venture with former US Oncology Research to expand clinical trial access across the country. It has conducted more than 850 first-in-human clinical trials since its inception and contributed to pivotal research that has led to the majority of new cancer therapies approved by the FDA in the past decade. SCRI’s research network brings together more than 1,300 physicians who are enrolling patients into clinical trials at more than 200 locations in 20+ states across the U.S. Please click here to learn more about our research offerings.
We care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse colleague population and ensure they are the healthiest versions of themselves. For more information regarding benefits through our parent company, McKesson, please click here.
As part of Total Rewards, we are proud to offer a competitive compensation package. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered.
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Originally posted on Himalayas