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Trax is a rapidly growing
company with start-up values

We started out with the daring mission of solving long-standing problems for our CPG and retail customers. Today, we are proud to be market makers, and our journey is streaked with perseverance, team work and a whole lot of fun.

Unleash your potential by joining a powerhouse of brilliant minds from diverse backgrounds, in an environment that is learning-friendly - and often filled with food!

SEE OUR CURRENT VACANCIES

Data Engineering Manager

Toronto · Full-time · Management

About The Position

Shopkick is on a mission to bring delight and reward to the consumer shopping experience. As part of the Trax Retail family, we are a unicorn looking to accelerate our growth trajectory as we partner with major brands and retailers, ranging from H&M and Unilever to Best Buy and Purina, to transform the way people engage with stores and products, both online and in the physical world. 

Shopkick is looking for a hands-on Data Engineering Manager who can bring their ideas, vision, and experience to build and manage our Data Engineering team. The ideal candidate has been a key contributor to building big data pipelines (Kafka, Streamsets, Spark, Airflow, DataFlow, DataFusion, etc) 

on GCP (BigQuery). This year, you’ll take ownership of our robust data platform, develop a long-term data infrastructure strategy, implement key improvements, and then build a world-class data engineering team. 

 

Essential duties and responsibilities may include, but are not limited to: 

  • Own the strategy, implementation and management of our data infrastructure. 
  • Build streaming and batch ETL pipelines to extract, transform, and load data from various sources. 
  • Create tools and automation to support our data analysts. 
  • Design a framework for ensuring data quality and governance.  
  • Help troubleshoot complex data issues and recommend solutions. 
  • Build and manage a strong data engineering team focused on delivering results and engineering excellence across the engineering lifecycle - design, build, test, release, and operate, i.e., a full ownership model. 
  • Communicate directions and decisions effectively with the team and stakeholders. 
  • Build alignment with engineering, analytics, and product leadership. 
  • Foster cross team communication ensuring data engineers work closely with the broader engineering team. 

 

Requirements

Qualifications: 

  • 2+ years of engineering leadership experience in at least a Sr, Lead, or Principal role. 
  • 5+ years of experience creating streaming and batch ETL systems 
  • Strong ability to write efficient SQL queries 
  • Strong coding ability in an object oriented language (Java, C#, C++, Python, etc.) 
  • Expertise with Google BigQuery, AWS Redshift, or AWS Athena  
  • Experience with message distribution systems like Kafka or Pub/Sub 
  • Familiarity with streaming ETL systems like StreamSets, Spark, DataFlow 
  • Excellent team player with strong communication skills (verbal and written) 
  • Enthusiastic about collaborative problem solving 
  • Eagerness to solve challenging problems and a love of learning and trying new things 
  • BS in Computer Science or related field or equivalent experience 

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