Senior Data Analyst

MIG Real Estate is looking for a Senior Data Analyst  to join our growing real estate team. Reporting to the CTO, you will be responsible for creating and operating a comprehensive data, reporting and visualization platform to support our acquisition, operation, and disposition of real estate assets. You will serve as a bridge between the business and the technical teams, and you will be a data analytics expert, including adopting and sharing best practice about collecting, cleaning, and organizing data to maximize our potential use of machine learning and AI.

You will need a high level of technical and business acumen, excellent communication skills, and a demonstrated ability to work in a fast-paced business environment.

At MIG Real Estate, data drives decision-making, and our team defines and interprets data to provide recommendations and perspectives to management and their teams. Our objective is to ensure that we have meaningful data and insights to make thoughtful decisions, most of which have a direct impact on our business. We also seek to build data fluency throughout the company.

In this role, you will work with a small team to expand and optimize our Microsoft Azure / Fabric data environment, including data pipeline architecture and Power BI-based dashboards and reports. The ideal candidate is an experienced data wrangler who enjoys working with multiple data sources, optimizing data architecture and semantic models, and working with users to ensure their business requirements are met using Excel and Power BI, including ad hoc queries and analysis.

As a key member of a small, growing team, you will also support other IT initiatives, including SharePoint and Teams enhancements, and tools to support automation of workflows and better collaboration.

• Manage the infrastructure for efficient ETL pipelines from a wide variety of data sources, primarily using SQL.
• Build analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics.
• Work with stakeholders across the firm to assist with data-related technical issues and support their data infrastructure needs.
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• Work with real estate colleagues to develop analytics and reporting to support our operations.
• Build and maintain AI-assisted workflows and reporting automations in collaboration with the automation team.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Take on projects to support development of strategy and measure its effectiveness.
• Own and govern shared Power BI semantic models deployed in Microsoft Fabric work spaces, ensuring accuracy, performance, and accessibility for business users.
• Partner with the data engineering and automation team members on pipeline design, ETL and semantic model optimization, warehouse structure, and delivery of analytics-ready datasets.

• Advanced experience developing in Power BI and DAX, including ownership of shared semantic models and report governance in a multi-user environment. Tabular Editor experience strongly preferred.
• Hands‑on experience with Microsoft Fabric, including lake houses, warehouses, and Fabric workspace administration.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience integrating Power BI with Excel, including CUBEVALUE-based reporting and Excel-as-reporting-layer patterns.
• Experience performing root‑cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Familiarity with financial accounting and cost accounting concepts.
• Strong analytic skills related to working with unstructured datasets (e.g., media, documents).
• Familiarity with the mechanics of data preparation, data handling, data warehousing, and similar projects.
• A successful history of manipulating,…