Analyst, Data Engineer, Firehouse Subs

Restaurant Brands International•Jacksonville, FL

1d•Onsite

About The Position

Restaurant Brands International Inc. is a global quick service restaurant company with multiple prominent brands including TIM HORTONS®, BURGER KING®, POPEYES®, and FIREHOUSE SUBS®. RBI is committed to growing its brands and improving sustainable outcomes through its Restaurant Brands for Good framework. The Analyst, Data Engineer will be responsible for designing, building, and maintaining data pipelines and ETL processes, and supporting the data engineering team with analytics, visualization, data governance, and ML. This role involves collaboration with Software Engineering, IT, and cross-functional stakeholders across Operations, Marketing, Supply Chain, and Finance to ensure data accuracy and consistency.

Requirements

1+ years of hands-on experience in data engineering, data analytics, or a related technical field.
Bachelor’s degree in computer science, engineering, or a related field; or equivalent experience
Experience with AWS, including key services such as S3, Glue/EMR, SQS, Step Functions, etc.
Strong programming skills in SQL and Python
Experience querying and building in Snowflake with dbt
Familiarity with version control, continuous integration, and infrastructure as code
Familiarity with a business intelligence reporting tools
Knowledge of Point of Sale and Back of House systems is helpful
Strong problem-solving and analytical skills
Clear communicator, able to work with cross-functional teams

Nice To Haves

Knowledge of Point of Sale and Back of House systems is helpful

Responsibilities

Support the design, build, and maintenance of efficient data pipelines and ETL processes to facilitate seamless data flow.
Help develop and maintain scalable data warehouse solutions to meet growing organizational data needs.
Monitor and troubleshoot data pipelines, identifying and resolving issues promptly and efficiently.
Model data tables and build business intelligence reporting dashboards.
Support the development and execution of the overall data engineering strategy set by the team, aligning with organizational goals.
Work with team and manager to continuously evaluate and implement new technologies and methodologies to enhance data engineering capabilities.