Sr. Data Engineer

Dedicated to innovative placemaking, Howard Hughes Communities is the real estate platform of Howard Hughes Holdings Inc. (NYSE: HHH) and is recognized for its ongoing commitment to design excellence and to the cultural life of its communities. Building on that foundation, we foster a culture of curiosity that empowers every employee to shape their own story within our organization.

About the Role

We are seeking a Sr. Data Engineer to design, build, and optimize enterprise data solutions across our Microsoft ecosystem. This role focuses on Microsoft Fabric, Power BI, and Azure data services (including Azure Data Factory, Azure Data Lake, and Azure SQL Database/Data Warehouse) to support analytics, operational reporting, and self-service BI across Howard Hughes Communities.

You will partner with business stakeholders, analysts, application teams, and infrastructure/security teams to create robust data pipelines, models, and platform standards that are scalable, secure, and support long-term growth.

This role reports to the Manager, Enterprise Application Development in our Corporate IT organization.

What You Will Do

Lead Power BI and semantic model strategy

• Design and develop Power BI environments, including workspace strategy, semantic models, data refresh patterns, and security (RLS/OLS).
  
• Create and support Power BI reports and dashboards, including maintaining and enhancing existing reports used by business and executive stakeholders.
  
• Support migration of current JD Edwards-based datasets and reports to Dynamics 365-based models, ensuring reconciled, trusted, side-by-side reporting during the transition.
  
• Define best practices for DAX, model design, and report performance; review and advise on designs for strategic reports and executive dashboards.
  
• Work with deployment pipelines and lifecycle management for BI content.
  

• Design and implement Lakehouse/Warehouse architecture in Microsoft Fabric to support analytics, operational reporting, and self-service BI.
  
• Build and orchestrate data pipelines using Microsoft Fabric and Data Pipeline to support ingestion, transformation, and automation scenarios.
  
• Working with REST/JSON APIs, connectors, and integration with SaaS platforms (including Dynamics 365, downstream applications etc.).
  
• Define canonical data models, shared dimensions, and reference data used across Fabric and Power BI.
  
• Support data transformations using SQL and Python as primary tools.
  
• Collaborate closely with analysts, business stakeholders, and application teams to ensure data solutions align with reporting, analytics, and operational requirements.
  

• Ensure data solutions are reliable, accurate, and performant, with appropriate monitoring, logging, and alerting.
  

• Bachelor's degree in computer science, Information Systems, Data Engineering, Data Science, Software Engineering, Applied Mathematics, or a related technical field; equivalent experience considered.
  
• 7+ years of experience in data engineering roles, with significant hands-on background in development/engineering background.
  
• Strong SQL and data modeling skills:
  
  • Design and optimization of relational and analytical models; complex queries and tuning.

• Experience with reporting and analytics for Dynamics 365
  
  • Building or supporting Power BI / Fabric-based reporting on top of D365 data.
    
  • Migrating reports and datasets from legacy ERP systems (e.g., JD Edwards) to Dynamics 365, including side-by-side reconciliation and validation
    
• Experience with Dynamics 365 (F&O and/or CE) and its integration capabilities:
  
  • Data entities, Dataverse, OData/REST APIs, webhooks, and export-to-data-lake patterns.
    
  • Understanding of core D365 data models and key financial/operational processes.
    
• Experience with additional Azure services (e.g., Azure Functions, Service Bus, Event Grid, API Management, Data Factory beyond Fabric scenarios).
  

• Competitive 401k plan
  
• Generous PTO policy
  
• Premium medical, dental, and vision coverage
  
• Voluntary benefits for unexpected life events
  
• Student loan assistance and stipends to assist with lifelong learning