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Lead, Data Governance, Information and Corporate Security (12-month contract)

Mid-Senior Level

Job Overview

Data Governance at CPP Investments is focused on enabling better decision-making through trusted, high-quality data.  The team maintains the enterprise-wide Data Governance Standard and works closely with Data Owners, Stewards, and Technical Area Leads (TALs) to ensure data products are fit for purpose, well-managed, and continuously improved.  We also partner with Stewards to ensure metadata is accurate, complete, and actionable, while providing guidance on implementing effective data quality rules and controls across the organization.

Job Description

As a lead, you are responsible for ensuring data governance standards are upheld while maintaining the quality, consistency, and interoperability of Data Products within the Enterprise Data Catalogue. Success in this role requires the ability to manage multiple initiatives simultaneously. You will provide technical guidance and support to a range of business partners, helping to drive the design and implementation of high-quality data products

Core Accountabilities:

  • An excellent role for someone who enjoy working with different teams, build relationships, provide consultation to identify, analyze, and resolve issues, as well as providing training and demos to help spread data quality benefits across the organization.
  • Provide consults to business and technology teams on data quality rule design and implementation.
  • Meet with business partners to foster good working relationships, understand their data quality needs and issues that they face, and work with data stewards and technology teams to find solutions.
  • Design data quality rules on AWS Glue Data Quality service.
  • Partner with data project leads, business analysts, and business partners to analyze data requirements and provide recommendation on data quality metrics, data quality rule design, and data model design.
  • Provide data modeling guidance by conducting data profiling and analysis using Python and Business Intelligence (BI) tools
  • Ensure new data quality enhancements address immediate business needs and in alignment with data strategy

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