Technical Disaster Lead

Duration: PermanentLocation: Calgary or Edmonton (3x/week, every august fully remote) Description Required Skills & Experience Undergraduate degree in Computer Science, Information Systems, or related field 7 years experience as a data/BI engineer including experience with Power BI or Tableau Must have experience in Retail Energy and working with Consumer Data Strong knowledge of fundamentals across data modeling and data architecture Strong understanding of dimensional and star schema data modeling (Databricks) Strong understanding of relational database concepts including SQL Thorough knowledge of data warehouse design and ETL Development methodologies and best practices Nice to Have Skills & Experience Certified Solutions Expert in Data Management and Analytics preferred Certified Data Engineer preferred Exposure to ML, data science, computer vision, AI, statistics, and/or applied mathematic Job Description Insight Global is looking for a Data Engineer to join a prominent Canadian diversified conglomerate that operates across multiple industries, including energy, utilities, structures & logistics, and investment. This will be a permanent, fulltime role, hybrid (3 days a week onsite) out of Edmonton or Calgary. On a daily basis, you’ll Design/develop solutions for dashboards Create automated dashboards that showcase demographics, campaign results, statistics, account histories, inventories, and other essential BI information Develop multiple views and integrate them into dashboards Develop, integrate and maintain the organizational data/reporting warehouse Work with the three lines of business to define KPIs, locate data, identify business rules, and deliver consistent and accurate data Write and optimize complex queries on large data sets Create and maintain data pipelines (ETL/ELT) from multiple sources Transform data and map to more valuable and understandable sets for consumption Troubleshoot issues related to data accuracy and create the source of truth Ensure data integrity and reliability by maintaining and enforcing security for sensitive data Use first- or third-party solutions to sync and automate processes for data refreshes Implement, manage and monitor error logging to make sure data is accurate and up to date Work to create algorithms and prototypes to support advanced analytics projects Identify and implement best practices to optimize data architecture and drive automation and performance efficiency Support development of Data Dictionaries and Data Taxonomy for existing project and master data management initiatives; document ETL process workflows for re-use.

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