Data Engineering Manager
Engineering | Toronto, Ontario, Canada | Full Time
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 pre-IPO 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.
- 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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