Data Process Automation Intern

ASSA ABLOYLake Forest, CA
1dHybrid

About The Position

Americas Residential, a division of ASSA ABLOY is seeking a highly motivated graduate student to join our team as a Data Analyst Intern. This role offers hands-on experience in building Power BI dashboards, supporting enterprise reporting initiatives, and contributing to enterprise data enablement projects. The intern will work closely with data, IT, and business stakeholders to help translate data into meaningful insights and improve data understanding across the organization. Must be available to work onsite in our Lake Forest office 3 days a week for our hybrid schedule – Tuesday, Wednesday and Thursday. Will be remote Mondays and Fridays.

Requirements

  • Currently pursuing a Master’s degree in Data Analytics, Data Science, Information Systems, Business Analytics, Computer Science, Business Administration, or a related field.
  • Basic to intermediate experience with Power BI (data modeling, visuals, filters, and measures)
  • Familiarity with Excel, or similar data analysis tools.
  • Understanding of data concepts such as datasets, metrics, KPIs, and data quality (preferred).
  • Strong analytical and problem-solving skills.
  • Detail-oriented with a focus on data accuracy and clear documentation.
  • Good communication skills and ability to collaborate with technical and non-technical stakeholders.
  • Eagerness to learn enterprise data platforms, reporting standards, and data governance practices.

Responsibilities

  • Support the design, development, and maintenance of Power BI reports and dashboards aligned to business needs.
  • Assist in gathering and documenting reporting requirements from business stakeholders and data owners.
  • Build and enhance Power BI visuals, datasets, and basic DAX measures following reporting standards and best practices.
  • Help validate data accuracy, perform basic data analysis, and reconcile source-to-report outputs.
  • Contribute to Data Literacy initiatives by documenting report definitions, KPIs, metrics, and business logic.
  • Support Data Catalog and Data Dictionary efforts by documenting datasets, fields, data definitions, and lineage information.
  • Partner with senior analysts and data engineers to understand data sources, models, and enterprise data structures.
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