Data Security Architect (IT)
Brandt
B randt 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 efficient data pipelines, ensuring data accuracy, and contributing to business intelligence initiatives.
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.
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.
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.
Architect the data models that feed PowerBI, enabling the creation of interactive, high-performance dashboards that provide actionable insights to stakeholders.
#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.
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.
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Focus Systems Inc.
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New Value Solutions
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