Data Engineer - Global Services, Data Apply
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 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. Were looking for people who are determined to make life better for people around the world.
Do you enjoy learning new knowledge domains and answering engaging questions?
The Global Services Tech at Lilly team is actively seeking a data engineer to partner with internal business and Tech at Lilly partners to accelerate the delivery of data solutions for analytics and business purposes.
What Youll Be Doing:
A data engineer is responsible for designing, developing, and maintaining the data solutions that ensure the availability and quality of data for analysis and/or business transactions. They design and implement efficient data storage, processing and retrieval solutions for datasets and build data pipelines, optimize database designs, and work closely with data scientists, architects, and analysts to ensure data quality and accessibility. Data engineers require strong skillsets in data integration, acquisition, cleansing, harmonization, and transforming data. They play a crucial role in transforming raw data into datasets designed for analysis which enable organizations to unlock valuable insights for decision making.
How Youll Succeed:
Engage and partner with cross-functional tech teams across Global Services (finance), third party solution delivery providers, and Data architects to understand the business problem and enhance/develop the appropriate data solution leveraging the modern tech stack
Design and implement highly performant data ingestion/processing pipelines from multiple sources
Develop technical solutions which combine disparate information to create meaningful insights for business partners
Operate with a quality mindset always considering the impact of design decisions on the long-term support and maintenance of data pipelines/jobs
Ensure data integrity, security, and privacy requirements are met
Stay abreast of tools and technologies to influence our strategy so that it provides best usage opportunities for business
What You Should Bring:
A foundational set of knowledge in: communication, leadership, teamwork, problem solving skills, solution / blueprint definition, business acumen, architectural processes (e.g. blueprinting, reference architecture, governance, etc.), technical standards, project delivery, and industry knowledge.
Strong skillsets in data integration, acquisition, cleansing, harmonization, and transforming data
Experience designing large scale data models for functional, operational, and analytical environments (Conceptual, Logical, Physical & Dimensional)
Experience in several of the following disciplines: statistical methods, data modeling, ontology development, semantic graph construction and linked data, relational schema design.
Demonstrated SQL/PLSQL and data modeling proficiency.
Experience with data modeling tools such as, ER*Studio and Erwin or TOAD
Experience in AWS or Azure techstack
Experience in building/integrating APIs
Experience in creating data products using APIs
Experience with security models and development on large data sets
Experience with multiple database technologies
Experience 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
Experience in implementing effective data loading strategy (CDC, incremental loads)
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, performance considerations & optimization, database versions, and database deployment strategies
Knowledgeable in data functions such as Data Governance, Master Data Management, Business Intelligence