DATA ENGINEERING SPECIALIST, CRM (HYBRID)

at  Green Shield

WHO WE ARE

When it comes to health, we’re always looking for ways to push for better. It’s why we were founded in the first place. In 1957, our founder, pharmacist William Wilkinson, witnessed a mother sacrifice her health by forgoing her own medicine to pay for her sick daughter’s prescription. He knew there had to be a better way. So, he introduced North America’s first prepaid drug plan, and GreenShield was born as a not-for-profit with a mission to support better health for all Canadians.
We aren’t just a health and benefits company. We’re the only not-for-profit social enterprise that brings worlds of coverage and care together, all in one place.
We’re noble challengers, purposefully building a better way and we need the best people to help us create a more holistic approach that takes care of the mind and body.
Our mission is to create better health for all Canadians, and we know that starts with our employees.

Reporting to the Director, Data Engineering & Operations, the Data Engineering Specialist will be a key member of GSC’s Data & AI team, helping to develop and support data strategy initiatives across the organization.

• Demonstrate creative thinking and innovation in the field of data management that enables enterprise-wide analytics
• Develop and implement data engineering best practices for data quality, data reliability, data access and data governance objectives
• Develop and implement data pipelines to assemble complex datasets
• Ability to transform and curate data from multiple sources and business domains for advanced analytics
• Translate business requirements into data solution implementation for business value creation
• Apply learnings to become a champion in building a long-term data strategy
• Collaborate with business and technology stakeholders in use case execution
• Work closely with data professionals within the organization (i.e., data architects, analysts, stewards, scientists) to define data architecture and tools for highly automated and reusable solution
• Build data platforms and capabilities required for optimal ETL pipelines across multiple data domains
• Support data governance and data quality pipelines by creating policies to ensure data integrity
• Support data management strategies and initiatives for long-term data needs of the organization