Data Architect (Regina)

Brandt is seeking a highly skilled and motivated Data Engineer to join our dynamic team. The ideal candidate will have a strong background in designing, implementing, and optimizing data solutions using PowerBI, Azure, and AI technologies. As a Data Engineer, you will play a crucial role in developing and maintaining productive data pipelines, ensuring data accuracy, and contributing to business intelligence initiatives. Duties and Responsibilities Data Architecture & Strategy - Data Solution Design: Lead the architectural design, data modeling, and implementation of highly scalable data processing systems within the Azure Data ecosystem. - Strategic Advisement: Partner with senior management and internal stakeholders to define data strategies, establish benchmarks, and translate complex business requirements into robust technical specifications. - Enterprise Capability Advancement: Drive the maturity of our enterprise data stack, defining best practices for data organization, governance, and architecture. Data Engineering & Optimization - Advanced SQL & Performance Tuning: Act as the team's primary SQL authority. Proactively identify, troubleshoot, and optimize inefficient queries, fine-tune execution plans, and ensure optimal database performance. - ETL/ELT Pipeline Development: Architect and maintain robust, scalable data pipelines to extract, transform, and load data from disparate sources into Azure Data Factory and Azure Data Lake Storage. - Workflow Streamlining: Continuously monitor and optimize data workflows to reduce processing times, minimize compute costs, and improve overall system efficiency. Business Intelligence & Security - Data Security & Governance: Implement strict data security measures, including encryption, robust access controls, and data masking to safeguard sensitive enterprise information. - PowerBI & Analytics Integration: Architect the data models that feed PowerBI, enabling the creation of interactive, high-performance dashboards that provide actionable insights to stakeholders. Required Skills - Deep SQL Mastery: Expert-level proficiency in SQL (T-SQL preferred). Must have hands‑on experience with query optimization, execution plan analysis, indexing strategies, complex joins, window functions, and CTEs. - Data Modeling: Strong background in relational and dimensional data modeling (Kimball/Inmon methodologies), data warehousing, and data dependencies across enterprise systems. - Azure Ecosystem: Deep expertise in Azure Data Factory, Azure SQL Database, and Azure Data Lake Storage. - Programming & BI: Highly proficient in Python and PowerBI (including DAX and Power Query optimization). - Emerging Tech: Familiarity with integrating machine learning models and AI tools into existing data workflows is a strong asset. Required Experience - 5–10 years of proven experience in Data Architecture, with a heavy emphasis on Microsoft Azure technologies. - Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent enterprise experience). - Demonstrated ability to break down complex, ambiguous processes and explain highly technical concepts to non-technical senior leadership. - Deep SQL Mastery: Expert-level proficiency in SQL (T-SQL preferred). Must have hands‑on experience with query optimization, execution plan analysis, indexing strategies, complex joins, window functions, and CTEs. - Data Modeling: Strong background in relational and dimensional data modeling (Kimball/Inmon methodologies), data warehousing, and data dependencies across enterprise systems. - Azure Ecosystem: Deep expertise in Azure Data Factory, Azure SQL Database, and Azure Data Lake Storage. - Programming & BI: Highly proficient in Python and PowerBI (including DAX and Power Query optimization). - Emerging Tech: Familiarity with integrating machine learning models and AI tools into existing data workflows is a strong asset. #J-18808-Ljbffr Apply on Kit Job: kitjob.ca/job/2okat7