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Sr. Data Architect

4 months ago

Marquand, Missouri, United States Eli Lilly Full time

At Lilly, we combine compassion with exploration to enhance the quality of life for individuals worldwide. We are a leading global healthcare organization with our main offices located in Indianapolis, Indiana. Our vast team works diligently across the globe to uncover and deliver groundbreaking medications to those in need, advance the comprehension and treatment of illnesses, and contribute to our communities through charitable endeavors and volunteer work. We are dedicated to our tasks, and we prioritize people above all else. We are searching for individuals who are passionate about improving the lives of others across the world.



Sr. Data Architect at Lilly

Company Overview
In the heart of Lilly, we intertwine caring and discovery to uplift the quality of life globally. Headquartered in Indianapolis, Indiana, we stand as a prominent figure in the healthcare industry. Our international team is on a mission to innovate, bring revolutionary medicines to those in demand, enhance disease management, and enrich our society through acts of generosity and voluntary work. At Lilly, we pour our hearts into our work, with a strong focus on prioritizing people. We are seeking individuals who are driven to make a positive impact on life around the globe.

Join us in revolutionizing Lilly's Quality Management System
Lilly has kicked off a complex QMS transformation initiative aimed at streamlining, standardizing, and enhancing QMS processes, fostering innovation and flexibility to accommodate unprecedented expansion across new sites, modalities, and collaborations, and modernizing solution infrastructure by transitioning to cloud-based platforms and cutting-edge technology. The Global Quality team at Lilly is actively seeking a Data Architect to contribute to the NextGen QMS Program.

Your Responsibilities
You will play a crucial role in shaping, designing, constructing, and upholding the data architecture vision, strategy, and principles for the NextGen QMS Program. You will set forth standards for naming, describing, overseeing, managing, modeling, transforming, and exploring data within Lilly's NG QMS solution. You will be a pivotal member of the Integration and Data Workstream within the NextGen QMS Program, with a primary focus on the QMS data dissemination strategy.

Keys to Success

- Collaborate with Lilly architects, software vendor, and third-party implementation partner to devise and implement a technical strategy for NG QMS data structure and data products.

- Engage with business stakeholders to pinpoint future applications for Lilly data and expected business outcomes, enabling processes to meet these requirements.

- Cultivate expertise in enterprise data domains, encompassing data associations, data quality, comprehension of business data needs, and the relevant technological tools and methodologies.

Leading in Architectural Aspects
  • Formulate comprehensive Data architectural blueprints and strategies for data products, durable analytical products, and AI solutions, ensuring alignment with business goals and technical viability.
  • Drive the design and implementation of scalable, robust, and secure data architectures to underpin the organization's data product array.
  • Provide technical leadership and counsel to cross-functional teams, ensuring compliance with best practices and architectural precepts.
  • Assume the role of a solution owner, defining non-functional prerequisites like alerting, monitoring, logging, etc., to ensure operational excellence.
Data Product Development
  • Collaborate closely with product management and business stakeholders to comprehend requirements and translate them into practicable technical solutions.
  • Steer the end-to-end development life cycle of data products, from conceptualization and design to implementation and deployment.
  • Promote innovation in data product development, persistently exploring emerging technologies and methodologies to enrich product capabilities and drive business value.
  • Lead product-oriented teams, concentrating on product development and directing teams in crafting data products.
AI Transformation Projects
  • Lead large-scale transformation endeavors centered on AI and machine learning, collaborating with business divisions to identify opportunities and outline project scope.
  • Architect and execute AI solutions utilizing machine learning algorithms, deep learning techniques, and other AI technologies to tackle intricate business dilemmas.
  • Ensure the seamless integration of AI solutions into existing systems and processes, propelling tangible business outcomes and fostering a culture of data-driven decision-making.
  • Work closely with manufacturing and quality leadership teams to champion the adoption of AI solutions, ensuring alignment with operational requirements and quality benchmarks.
AI Persistent Pod
  • Lead the support and enhancement of AI solutions from a persistent pod perspective.
  • Establish Operations Metrics, define metrics for Model effectiveness, gauge data drift, and uphold operational stability of models.
  • Collaborate with the persistent pod, including vendors, to address outages, issues, etc.
  • Collaborate closely with manufacturing and quality leadership teams to update and align on operational requirements and quality norms.
Enhancing Cross-Functional Collaboration
  • Efficaciously collaborate with cross-functional teams, including data scientists, engineers, analysts, and business stakeholders, to deliver integrated solutions that cater to business needs.
  • Serve as a trusted consultant to senior leadership, offering insights and suggestions on technological trends, industry best practices, and strategic prospects in data and AI.
  • Mentor junior talents, providing direction and assistance in technical skill advancement and project implementation.
Engagement with Vendors and Partners
  • Cooperate with vendors and partners to leverage external expertise and technologies, ensuring harmony with organizational objectives and standards.
  • Evaluate and select suitable vendors and partners to back data and AI initiatives, fostering strong rapport and driving successful outcomes.

- Gain insight into how enterprise data strategies, platforms, and technologies facilitate business execution. Deploy this knowledge to challenge the status quo appropriately and cultivate business partnerships and collaborations.

- Regularly scout the technology landscape for novel trends and methods; interact with external consultants and thought leaders as necessary.

- Formulate innovative scalable approaches for Lilly data integration; construct compelling arguments, communicate, and elucidate the rationale for new approaches to fellow engineers and senior management.

- Possess an in-depth understanding of how data is or will be utilized and its implications on individuals, processes, capabilities, and technologies, including analytics and data integrations.

- Collaborate closely with data generators, information management, data engineers, AI/ML engineers, and data consumers.

Essential Requirements

- Demonstrated proficiency in communication, leadership, teamwork, project execution, and issue resolution skills.

- Proficient in architectural procedures (e.g., blueprinting, reference architecture, governance, etc.).

- Familiarity with external data standards (e.g., HL7, CDISC, SDTM) and external data terminologies (e.g., MedDRA, RxNorm, SNOMED).

- Proficiency in data modeling, data warehousing, data integration, data governance, and an understanding of data security, data standards, and cloud architecture principles.

- Proven ability to steer IT and business strategies to achieve large-scale results.

- Validated skills in rapid learning and relationship cultivation to drive change utilizing knowledge and relationships.

- Track record of delivering high-quality, user-centric, timely, and cost-effective IT services and project deliverables.

- Experience with formal project management methodologies, agile frameworks (e.g., Scrum, Kanban, SAFe, etc.), and working knowledge of associated practices and tools.

- Exceptional analytical, problem-solving, and communication skills, collaborating across agile and diverse teams.

- A keen sense of intellectual curiosity, external perspective, and interest in innovation.

- Proficiency in designing extensive data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional).

- Experience with data modeling tools like Erwin Data Modeler, ER/Studio, Lucidchart, etc.

- Expertise in several disciplines such as statistical methods, data modeling, data administration, ontology development, semantic graph construction, and linked data, relational schema design.

- Demonstrated aptitude in SQL/PLSQL and data modeling.

- Proficiency in AWS, Azure techstack, and other cloud technologies.

- Experience with security models and development regarding large data sets.

- Proficiency in working with a variety of relational and non-relational databases.

- Competence with multiple database solutions (e.g., Postgres, Redshift, Aurora, Athena) and formal database designs (3NF, Dimensional Models).

- Experience with Agile Development, CI/CD, Jenkins, Github, Automation platforms.

- Proven ability to dissect extensive, complex data domains and formulate practical solutions for subsequent data utilization through analytics.

- Demonstrated ability to communicate with a dispersed group of business and technical peers.

- Ability to review and propose practical suggestions on design patterns, performance considerations & optimization, database versions, and database deployment strategies.

- Proficient in data functions like Data Governance, Master Data Management, Business Intelligence.

- Experience in migrating on-premises solutions to the cloud and knowledge in multiple data ingestion methods.

Primary Criteria

- Bachelor's Degree in computer science or a related scientific area.

- Over 10 years in a senior-level solutions architecture role, focusing on data products and AI transformation projects.

- Extensive Analytics experience (over 10 years) in developing/leading Data integration, Data curation, and Data consumption domains.

- Hands-on experience (more than 5 years) with AI and machine learning technologies, including familiarity with popular ML frameworks (e.g., TensorFlow, PyTorch) and algorithms.

Additional Preferences

- Acquaintance with GxP, Pharmaceutical manufacturing processes, and automation systems.

- Practical Experience (over 1 year) with Gen AI models (Open AI)

- Over 10 years of relevant work experience.

- Experience in regulated environments and adhering to internal systems quality protocols and procedures.

About the Company
Lilly IT leverages cutting-edge technologies akin to major tech enterprises. What sets Lilly IT apart is our commitment to leveraging technology to propel our mission - crafting medicines that enhance the lives of people globally, such as data-driven drug discovery and interconnected clinical trials. We recruit premier technology experts from diverse backgrounds to bring a wealth of knowledge, skills, and varied perspectives to deliver innovative solutions across all facets of our enterprise. Lilly is poised for significant growth, and we remain steadfast in our dedication to delivering groundbreaking medicines to patients worldwide. Lilly is making substantial investments worldwide to establish state-of-the-art manufacturing facilities and expand our existing sites to create the necessary capacity to further our mission. The novel facilities will employ cutting-edge technology, advanced highly integrated and automated manufacturing systems, and will prioritize minimizing our environmental footprint.