• Architect relational and multi-dimensional databases from structured, semi-structured and unstructured data with development techniques including star and snowflake schemas, ETL, Slow Changing Dimensions (SCD), Fact and Cube development in a data management framework in conjunction with the Provincial Data Platform Infrastructure.
• Identify, design and implement internal process improvements: automate manual processes, optimize data delivery, re-design data pipelines for greater scalability.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiencies, and other key business performance metrics.
• Develop, maintain, optimize, troubleshoot, debug, monitor, backup and recovery operations for the ETL environment.
• Analyze datasets to ensure compliance with data sharing agreements and legislation restrictions, and for alignment with data architecture guidelines.
• Mentor, support and train Information Analyst and Junior Data Management resources, as required.

Qualifications
• Have a minimum of five (5) years of proven experience working as a Data Engineer or similar role.
• Possess a bachelor’s degree in information technology, Engineering or Computer Science, or a diploma in related data management/information technology stream with three (3) additional years of experience (over the required five (5) years) working as a Data Engineer or similar role.
• Have a minimum of two (2) years of proven experience using Informatica software (i.e., Power Centre, Integration Services, Workflow Manager, IDMC and TDM) in an integrated support environment.
Expert knowledge of:
• Oracle and SQL Server Database Management Systems and tools.
• ETL and data pipeline development experience; providing technical consulting and guidance to development teams for the design and development of highly complex or critical ETL architecture.
• Computer programming languages such as PL/SQL, R, Python.
• Operating systems such as Unix, Linux, and Windows.
• Shell Scripting language.
• Data Application Programming Interface (API).
• Algorithms and data structures.

Summary
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