Intern - Data Engineering (Data Analytics, Information Sciences, Computer Science Majors)

Simon Property GroupSimon Property GroupIndianapolis, Indiana, United States
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Posted

9/4/2026

Employment

Intern

Range

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Work style

On-site

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AI summary

Core responsibilities

The intern will build and maintain data pipelines, data models, and dashboards to support business decision-making. They will also collaborate with data scientists and analysts to improve data quality and present project findings to the team.

Requirements overview

Candidates must be pursuing a Bachelor's or Master's degree in a relevant field such as Computer Science, Data Analytics, or Information Systems. Proficiency in SQL and Python, along with exposure to BI tools, is required.

Key skills

SQLPythonData EngineeringData ModelingData PipelinesPower BISnowflakeMicrosoft FabricData QualityData AnalysisDashboard DevelopmentCommunication

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Education requirements

bachelor degreepostgraduate degree

About Simon Property Group

Industry

Real Estate

Employees

3,879

Type

Public Company

Size

5,001-10,000 employees

Simon is a global leader in the ownership of premier shopping, dining, entertainment and mixed-use destinations and an S&P 100 company (Simon Property Group, NYSE: SPG). Our properties across North America, Europe, and Asia provide community gathering places for millions of people every day and generate billions in annual sales. Our portfolio includes assets of national and international renown - proven assets that are the preferred location for retailers. In addition to our high quality properties, Simon is also known for our strong balance sheet, a long-tenured and well-respected senior management team, and our innovative spirit, as reflected in a 50 + year history of successful retail real estate development, management & leasing. Employment at Simon is considered the pinnacle of a career by real estate professionals due to our leadership position in the industry. With a total market capitalization of over $80 billion, we are well positioned to continue to deliver strong financial results and create shareholder value. Headquartered in Indianapolis, Indiana, we employ approximately 4,800 people across the United States.

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Job categories

Data & AnalyticsTechnologySoftwareEngineering

Description

Job Location: Corporate Indianapolis Simon is looking for a Data Engineering Intern to help build the data models, data pipelines, semantic models and dashboards our business runs on. You'll work alongside data engineers, data scientists and BI developers to turn raw data from marketing, media, leasing, operations into clean, trusted datasets that decision-makers actually use. This is a hands-on data engineering internship. You'll write real SQL, ship real models, and see your work land in front of business stakeholders. RESPONSIBILITIES • Build data pipelines to connect to and ingest data from various data sources • Build, enhance, document data models in our Fabric and Snowflake data platforms • Profile source data, investigate discrepancies, and improve data quality • Partner with analysts to translate business questions into reusable datasets • Build/enhance data agents as needed • Develop and refine dashboards and reports in Power BI as needed • Present your summer project and findings to the Data & Analytics team QUALIFICATIONS • Pursuing a Bachelor's or Master's in Data Analytics, Information Systems, Computer Science, AI, Statistics or a related field • Working knowledge of SQL (joins, aggregations, window functions) • Working knowledge of Python for data manipulation • Exposure to a BI tool (Power BI, Tableau, Looker) through coursework, projects, or prior internships • Clear written and verbal communication; comfort asking questions and explaining your reasoning • Strong attention to detail and genuine curiosity about how a business works

Requirements

  • SQL
  • Python
  • Data Engineering
  • Data Modeling
  • Data Pipelines
  • Power BI
  • Snowflake
  • Microsoft Fabric
  • Data Quality
  • Data Analysis
  • Dashboard Development
  • Communication

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