The Data Engineering team is looking for people who are passionate about data and are looking to bring their expertise in big data and cloud by working in agile delivery environments to resolve engineering challenges of building robust and scalable data systems aligned to our enterprise data strategy.
As a Lead, Data Engineer - you will be responsible for understanding the business requirements and translate the data engineering and analytics needs to support the development, construction and testing of large-scale data processing systems based on AWS cloud to help address the disparate data consumption / integration / operation challenges of a growing organization.
By supporting investment professionals, you will see first-hand how your contribution is delivering long-term value to the CPP Fund for the benefit of 20 million CPP contributors and beneficiaries. You are encouraged to bring an innovative mindset to tackle complex business requirements in the investment industry.
Role-specific Accountabilities
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Design solutions aligned with long-term architecture and technology strategy using Amazon Web Services (AWS) for Cloud development
Participate in the development life cycle from start to completion - requirements analysis, development, testing, and deployment
Work with data analysts to select and acquire non-traditional datasets and access, clean, and pre-process data as required by use cases
Select appropriate datasets and data representation methods
Collaborate with data analysts to have necessary data pipelines built
Build, train, validate and test models using criteria relevant to business objectives
Work in a fast-paced environment collaborating with data analysts, data engineers and architects
Ensure architecture will support the requirements of CPP Investments business
Prepare, transform, combine and manage structured and unstructured data for use by CPP Investments business users
Recommend ways to improve data reliability, efficiency and quality
Define and shape CPP Investments future technology and research process
University degree in Engineering or Computer Science preferred
Proven ability to work independently as well as to perform effectively in a team-oriented and open-concept environment