Technical Data Integrator at Lilly

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

31 Jan, 26

Salary

0.0

Posted On

02 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Integration, ETL, Cloud Platforms, AWS, Azure, GCP, Data Warehousing, Big Data Technologies, Master Data Management, Analytical Skills, Problem-Solving, Communication Skills, Documentation Skills, Teamwork, Technical Consultation

Industry

Pharmaceutical Manufacturing

Description

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. We’re looking for people who are determined to make life better for people around the world. Job Summary At Lilly, we’re, inspired to make a difference in people’s lives every day – through the discovery of life-changing medicines, better understanding of disease management and support for people living with illness and their families and friends. Our work today – from our research programs to our volunteer initiatives – reflects our heritage of uniting caring with discovery to make life better for people around the world. We invite you to explore career opportunities with Eli Lilly Canada, where we work together to make life better for people. You have an opportunity. The Technical Data Integrator plays a crucial role in ensuring that data from various systems, platforms, and sources is seamlessly connected, transformed, and made usable for business operations, analytics, and decision-making. The Technical Data Integrator is responsible for designing, developing, and maintaining data integration solutions that enable the efficient flow of data across enterprise systems. This role involves working closely with data architects, business analysts, and IT teams to ensure data consistency, quality, and availability for operational and analytical purposes. Key Responsibilities 1. Strategic Integration & Architecture Anticipate the implications of technical decisions on partners’ business, TECH@LILLY business, and the TECH@LILLY portfolio. Understand the development of Enterprise Architecture, focusing on interoperability across TECH@LILLY disciplines. Anticipate the implications of data integration decisions on business operations, compliance, and system interoperability. Carry projects through the necessary triage and governance (Tech@lilly and global) 2. Technical Implementation & Solution Design Enable effective information flows across TECH@LILLY and partner business processes. Implement innovative approaches for integrating new technologies supporting business transformation. Provide guidance to project teams on designing and implementing solutions and tools for optimal enterprise use. Use standardized processes for requirements definition, analysis, design, construct, and test activities. Provide technical consultation across technologies to internal technology and business area partners. Ensure data quality, consistency, and governance across integrated systems. 3. Incident & Change Management Collect relevant information required to resolve incidents raised by business partners or system users within committed service levels. Analyze series of incidents to identify problems. Ensure change requests in compliance with local change control procedures. Support the recording and reporting of status of items and modification requests. Define/improve change control process. Resolve data-related incidents and manage change requests within committed service levels and ensure that SLAs are met. 4. Collaboration & Stakeholder Engagement Collaborate with architects, developers, and business stakeholders to define data requirements and integration strategies. Support and/or contribute to the design, development, and delivery of end-user training and/or procedures. Support and contribute to end-user training and documentation related to data integration processes. Anticipate the implications of technical decisions on all parts of the TECH@LILLY portfolio, timelines and influence life-cycle decisions accordingly. Required Skills & Qualifications: Education: Bachelor’s degree in Computer Science, Information Systems, or related field. Experience: 3–5+ years in data integration, ETL, or related roles. Technical Skills: Experience with ETL tools and data integration platforms. Knowledge of cloud platforms (AWS, Azure, GCP). Understanding of data warehousing and big data technologies. Knowledge of master data management (MDM) principles. Certifications in data integration tools or cloud platforms. Soft Skills: Strong analytical and problem-solving abilities. Excellent communication and documentation skills. Ability to work independently and in teams. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status. #WeAreLilly

Responsibilities

The Technical Data Integrator is responsible for designing, developing, and maintaining data integration solutions that enable the efficient flow of data across enterprise systems. This role involves working closely with data architects, business analysts, and IT teams to ensure data consistency, quality, and availability for operational and analytical purposes.