Global Business Intelligence Solutions Data Architect

About This Role

This data architecture role supports digital transformation within the Global Business Intelligence Solutions (GBIS) group by designing and developing data engineering and integration solutions. It involves drafting specifications, creating solution designs, and coordinating with development teams, while also advising on complex analytics design to align with Data and Analytics Hub principles, standards, and strategies.

Responsibilities

• Use leadership skills to drive process, data, analytics, and AI design from discovery to delivery
• Collaborate with Business and GIS stakeholders to support big data platform initiatives and provide direction on defining data strategy and architecture for cloud-native platforms
• Design and develop data engineering solutions and data governance specifications as part of digital transformation processes
• Participate in business transformation workshops with subject matter experts to identify data and process gaps, proposing scalable data and analytics architectures to address those needs
• Utilize existing architecture as a data hub for the digital transformation program, identifying supplemental tools and services for process improvement
• Offer guidance and insights on emerging data analytics trends and technical capabilities that can enhance digital transformation across the company
• Demonstrate advanced data and analytics solutions to digital transformation teams, showing the potential of the Data Fabric platform with proof-of-concept projects
• Develop, uphold, and advocate for advanced analytics standards and procedures throughout the GIS Data Hub across the entire organization
• Design planning and analytics solutions by integrating Workday Adaptive with the Azure analytics stack (Microsoft Fabric, Synapse, Power BI), including ETL/ELT pipelines to support enterprise decision-making
• Build strong relationships with key business sponsors and IT resources to efficiently resolve work requests

Requirements

• Bachelor’s degree in Computer Science, Information Technology, MIS, Data Science, Analytics, or a relevant Engineering field; Master's or PhD preferred
• Over 12 years of experience with modern data engineering, data warehousing, and data lake technologies on cloud platforms such as Azure, AWS, and Databricks
• Over 10 years of SQL experience with cloud-native data warehousing and data modeling
• Over 5 years of experience in building and supporting FP&A applications, integrating platforms such as Workday Adaptive, Anaplan, SAP BPC etc. with ERP systems and Azure data platform
• Over 5 years of experience configuring Azure cloud and SaaS platforms and building automated ETL/ELT pipelines for real-time, streaming and batch data exchange
• Minimum of 3 years working extensively with Spark and Python technologies for big data processing