Overview

Enterprise Services provides strategic workplace solutions and robust infrastructure to deliver a consistent employee experience globally.

Responsibilities

• Develop and optimize trusted data models and shared semantic models that standardize core entities, dimensions and metrics across physical and digital workplace reporting.
• Create and maintain Power BI datasets, dashboards, reports and analytical tools that enable leaders and operational teams to understand employee experience, technology performance, space utilization and workplace operations.
• Enable secure self-service analytics and responsible data use through reusable datasets, clear documentation and appropriate access controls, aligned with privacy, audit and InfoSec standards.
• Implement data quality, lineage, testing and observability controls, investigating issues and working with source-system owners to resolve root causes.
• Define, develop and maintain automated, monitored and well-documented analytical transformations and reporting processes, partnering with the pipeline engineer on upstream dependencies to improve reliability, refresh performance and time from source data to decision-ready insight.
• Partner with a pipeline engineer to define data ingestion, integration and transformation requirements across digital workplace platforms, workplace technology, occupancy and space systems, facilities and operational sources.
• Partner with product managers, analysts, technology teams and workplace stakeholders to translate business questions into clear technical requirements and reliable data solutions.
• 3–6 years of experience in business intelligence, analytics engineering, data engineering or a related discipline, including delivery of production-grade data and reporting solutions.
• Knowledge of data visualization best practices and design principles to create clear, engaging insights that communicate the story, highlight what matters and support decision-making.
• Strong SQL skills and practical experience designing, querying and optimizing relational, dimensional and analytical data models.
• Experience partnering with data or pipeline engineers to specify source, ingestion, transformation and integration needs across APIs, files, databases and cloud platforms, and to validate that resulting datasets meet analytical requirements.
• Experience developing Power BI semantic models, reports and dashboards, including Power Query and performance optimization.
• Understanding of software engineering practices including version control, testing, deployment, monitoring and technical documentation.
• Ability to analyze complex datasets, identify quality issues and trends, and explain technical findings clearly to business and technology stakeholders.
• Strong collaboration and problem-solving skills, with the ability to gather requirements and deliver maintainable solutions that support business outcomes.
• Hands-on experience with Microsoft Fabric, Azure data services and related Microsoft analytics tooling.
• Experience with Python or another scripting language for data transformation, automation and quality validation.
• Knowledge of workplace data domains such as Microsoft 365 and endpoint experience, service management, occupancy, space, building, facilities or employee experience data.
• Familiarity with metadata management, data catalogs, master and reference data, privacy, security and role-based access controls.
• Understanding of APIs, workflow orchestration, CI/CD and modern cloud data architecture patterns.