Data Architect, Gra

2 weeks ago

Bengaluru, India Lilly Full time

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 35,000 employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

Medicines Development IDS (MD IDS) serves as a strategic function within Lilly Research Laboratories (LRL) partnering with the Medicines Development Unit (MDU). The MDU focuses on taking potential marketable products from Research through product registration and approval. As part of MDU, Global Regulatory Affairs (GRA) develop and execute regulatory strategy, lead interactions with regulatory boards and collaborate with Lilly colleagues. The GRA team provides deep expertise in regulatory sciences which helps to quantify risk and help influence decision-making by Lilly leaders.

The role of the GRA Data Architect is responsible for ensuring the availability and quality of data needed for regulatory analysis. This includes working with data scientists and engineers to create a deep understanding of the relevant data domains and relationships, modeling new and existing data in new ways to meet business needs, suggesting technics for harmonizing disparate data sources and new approaches to analyzing the data. Responsible for the understanding new data requirements then working in conjunction with the development team to build, test, document and maintain the data solutions that are both scalable and supportable.

**Key Objectives and Deliverables**:
**Data Architect Responsibilities**
- Create and maintain Data Information Vision and Strategy, which includes the ability to work with business to identify future uses for Lilly data and anticipated business results and enable processes to support these needs.
- Create and maintain Data Planning/Modelling and Data Lifecycle Design. This includes the ability to develop a technical strategy for future data structure and data integration.
- Develop and provide expertise in enterprise data domains; this includes data relationships, data quality, understanding of business data needs and the associated technology toolsets and methodologies.
- Develop understanding how the enterprise data strategies, platforms, and technologies enable business execution. Use this knowledge to appropriately challenge status quo and drive business-IT collaboration.
- Analyze data from multiple domains; discover trends and associations, synthesize new integration constructs that assist non-expert users to find similar trends and associations.
- Facilitate efficient and scalable data exchange between Lilly and its external partners using industry standards and data integration methodologies.
- Use cutting edge information technologies to organize and analyze data
- Extend publicly available data sets, ontologies and taxonomies for internal Lilly use.
- Continuously scan the technology environment for new trends and techniques; interface with external consultants and thought leaders as needed.
- Synthesise new scalable approaches for Lilly data integration; derive the supporting arguments, communicate and articulate the reasons for the new approaches to fellow engineers as well as senior management.
- Work with Computer Systems Quality team to validate solutions.
- Identify, troubleshoot, debug, and resolve technical issues.
- Work in Agile Sprints with business facing project teams

**Basic Qualifications**:

- Bachelor’s Degree in computer science or related scientific discipline.
- 10+ years of experience designing large scale data models for functional, operational and analytical environments (Conceptual, Logical, Physical & Dimensional)
- 7+ years’ experience in several of the following disciplines: statistical methods, data modeling, ontology development, semantic graph construction and linked data, relational schema design.
- Demonstrated SQL, data and object modeling proficiency.
- Experience in AWS cloud-based data solutions.
- Experience with security models and development on large data sets
- Design experience in multimodel systems
- Experience with multiple database solutions (e.g. Postgres, Redshift, Aurora, Athena) and formal database designs (3NF, Dimensional Models)
- Experience or knowledge in semantic model development with graph technology
- Demonstrated ability to analyze large, complex data domains and craft practical solutions for subsequent data exploitation via analytics.
- Demonstrated ability to communicate with a geographically dispersed group of business and technical colleagues
- Ability to review and provide practical recommendations on design patterns
- Experience working directly with business partners for

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