Data Engineer II, Tim Hortons, Canada

Restaurant Brands International•Toronto, ON

5d•CA$90,000 - CA$110,000•Onsite

About The Position

Restaurant Brands International Inc. (RBI) is seeking a skilled Data Engineer II to join their Tim Hortons team in Canada. This role is crucial in building and maintaining scalable data pipelines and data platforms to support analytics and business insights. RBI is one of the world's largest quick service restaurant companies, owning iconic brands like TIM HORTONS®, BURGER KING®, POPEYES®, and FIREHOUSE SUBS®. The company is committed to growing its brands through leveraging core values, strong relationships, and community support, while benefiting from global scale and shared best practices. This position requires a passion for working with large-scale data systems and contributing to the company's dream of building the most loved restaurant brands in the world.

Requirements

Minimum under graduation degree or equivalent in Computer Science Engineering, Statistics, Mathematics, or related technical field
2+ years of experience in programming languages like Python, SQL, Scala
2+ years of experience in designing complex Realtime / batch data pipelines
2+ years of experience in Big Data Space – Apache Spark / HDFS / Hadoop / Hive
2+ years of experience in designing CI/CD pipelines through Terraform / Git
2+ years of experience in building scalable cloud-based data pipelines using Lambda, Glue, Dynamo, IAM
Strong problem-solving skills with an emphasis on product development
Ability to manage in an environment of quick change
Outcome focused, critical thinkers with the ability to analyze and visualize
Ability to work in a fast-paced Agile environment
Transparent and professional communication

Nice To Haves

Experience with Snowflake (data warehousing / data modeling / performance basics)
Experience with Databricks
Experience with Loyalty Programs

Responsibilities

Design, develop, and maintain scalable and reliable data pipelines using Python and Apache Spark
Build and optimize ETL/ELT workflows to process structured and unstructured data
Work with AWS services (such as S3, EC2, Dynamo, Glue, Lambda) to deploy and manage data solutions
Implement and manage data warehousing solutions using Snowflake
Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements
Implement best practices across data industry to standardize and automate data pipelines
Implement security and governance guidelines and ensure compliance to regulations