Data Architect - Life Science - Manager- Consulting
Listed on 2026-01-01
-
IT/Tech
Data Engineer, Data Science Manager
Data Architect - Life Science - Manager
- Consulting (Location OPEN)
Join to apply for the Data Architect - Life Science - Manager
- Consulting - Location OPEN role at EY
Location:
Anywhere in Country
At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help build a better working world.
Technology – AI & DataEY delivers unparalleled tech consulting services in data strategy, business intelligence, digital, machine learning and Artificial Intelligence. We support and enable big ideas, always with the ambition to keep doing more.
The opportunityEY is seeking a Data Architecture Manager, with a strong understanding of data and technology within the Life Sciences (Clinical (R&D) and Commercial) sector, complemented by a solid track record of delivery. This individual will spearhead the design, development, and governance of our clients’s data architectures, ensuring scalable, effective, and secure data solutions that align with business objectives and support data imperatives.
You will have the opportunity to lead and develop your skill set to keep up with the ever‑growing demands of the modern data platform. This is a high growth area and a high visibility role with plenty of opportunities to enhance your skillset and build your career.
As a Manager in Data Architecture, you will lead transformative technology projects and programs that align with our organizational strategy to achieve impactful outcomes. You will provide assurance to leadership by managing timelines, costs, and quality, and lead both technical and non‑technical project teams in the development and implementation of cutting‑edge technology solutions and infrastructure.
YourKey Responsibilities
- Design and build scalable solutions for life sciences clients that unify, enrich, and derive insights from varied data sources across a broad technology landscape.
- Help clients navigate the complex world of modern data science, analytics, and software engineering.
- Provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support ongoing business needs.
- Manage and deliver one or more processes, solutions, and projects, focusing on quality and effective risk management.
- Drive continuous process improvement and identify innovative solutions through research, analysis, and best practices.
- Interpret internal/external issues to recommend quality solutions and guide others.
- Collaborate with cross‑functional teams to define data requirements, design solutions, and implement data strategies.
- Organize and lead workshops and design sessions with stakeholders to capture requirements and align on data architecture strategies.
- Design and build solutions on AWS, Databricks, Snowflake.
- Design conceptual, logical, physical layers of a data solution.
- Conduct data design reviews, striving for improved usability and efficiency.
- Design blueprints for data extraction and basic transformations.
- Participate in presentations and proposals for highly complex projects.
- Apply technical skills in integration with third‑party vendor SaaS applications.
- Apply cloud computing and architecture principles.
- Implement data integration best practices and develop standardized practices for delivering new products and capabilities using Big Data technologies.
- Interact with senior client technology leaders to create, architect, propose, develop, and deliver solutions.
- Define and develop client‑specific best practices around data management within Hadoop or cloud environments.
- Recommend design alternatives for data ingestion, processing, and provisioning layers.
- Experience in enterprise‑grade solution implementations, BI, and data analytics databases.
- Convert business problems to technical solutions considering security, performance, scalability.
- Knowledge of big data architecture patterns (Lambda, Kappa).
- Experience in performance benchmarking enterprise applications.
- Experience in data security (on‑the‑move, at‑rest).
- Bachelor’…
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