Enterprise Data Architect - Azure / ETL

Key Responsibilities:

• Lead Data Architecture
• Design, develop, and implement comprehensive enterprise data architectures, primarily leveraging Azure and Snowflake platforms.
• Data Transformation & ETL
• Oversee and guide complex data transformation and ETL processes for large and diverse datasets, ensuring data quality, consistency, and performance.
• Customer-Centric Data Design
• Design and optimize datasets sourced from CRM, Call Center, Marketing, Offline, and Point of Sale systems to meet customer-centric business needs.
• Data Modeling
• Drive the development and maintenance of relational, dimensional, columnar, and big data models to support both operational and analytical use cases.
• Query Optimization
• Develop and troubleshoot complex SQL and NoSQL queries to ensure optimal performance and data accessibility.
• Data Warehouse Management
• Apply best practices in data warehousing to build and manage scalable, high-performing warehouse environments.
• Tool Evaluation & Implementation
• Evaluate, recommend, and implement industry-standard ETL tools such as Informatica and Unifi to align with enterprise data strategy.
• Business Requirements & Analysis
• Lead structured analysis, use case documentation, and process design to translate business requirements into scalable data solutions.
• Reporting & Analytics Support
• Provide architectural guidance to reporting teams using tools like Tableau and Power BI.
• Software Development Practices
• Apply standard software engineering practices to data solutions, ensuring code quality, version control, and documentation.
• Stakeholder Collaboration
• Collaborate with internal sales teams and engage directly with clients to understand their data challenges and deliver strategic outcomes.
• Project Management & Multi-tasking
• Manage and prioritize multiple concurrent projects, demonstrating strong organizational skills and the ability to meet tight deadlines.
• Strategic Thinking & Leadership
• Lead continuous improvement initiatives, staying proactive, self-managed, and focused on driving business value through data architecture.