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Sr Data Engineer

Posted on: October 29th, 2019 Kelowna, BC Strawhouse

About Uncoil:
Out of the fires that forged Strawhouse; Canada’s fastest growing Startup of 2017, comes Uncoil, a Startup that is taking the confusion out of data visibility & interpretation for eCommerce brands. Leveraging the power of machine learning and real time data-pipelines, we unify disparate data sources - turning them into actionable insights for Digital Brands. Uncoil combines robust data visualization and recommendation tools to solve marketing & business problems. Goodbye spreadsheets, goodbye pivot tables, goodbye not knowing what to action on. 

The Extras

  • We are a sister company to Strawhouse - one of the largest Canadian based Facebook advertising partners and Canada’s Fastest Growing Startup in 2017.
  • We encourage everyone here to ‘be themselves’. Our strength comes from our diversity. This means a casual office dress code and environment.
  • We are headquartered in downtown Kelowna, BC, with an office filled with high performing peers.
  • We offer snacks, drinks, team lunches on Fridays and all the other tech co accoutrement, billiards, ping pong etc

The Opportunity

You enjoy rolling up your sleeves and getting right into the code. You desire and strive to build platforms and products people love. You have a highly proven track record to fit into becoming a reliable development team contributor across the stack with a keen interest and skills in backend development, infrastructure, scalability, performance and data science implementation. 

In this role, you will be a key part of the engineering team and a major contributor to our sprint velocity. You will be a key member to bridge the Data Science Department and Engineering team to be held accountable for the deployment, and implementation of the Data Science models to feed into our insights engine. You enjoy being a key resource to make data related decision and push the evolution of our implementation of new data sources and data science models to new heights.

The Work

  • Working on a data pipeline that fetches data from third-party APIs, leveraging Apache Kafka, Apache Parquet and Apache Spark SQL
  • Develop new Apache Spark queries as needed using Spark SQL
  • Work with our data science team to productionize machine learning logic using Spark MLLib, deep learning libraries, and in house built models built in python.
  • Improve data pipeline for scale and efficency.
  • Deploy data pipeline on Kubernetes using Google Cloud Platform
  • Continuously learning the latest best practices and technology standards to ensure we are always using the highest leverage tools and techniques possible. 
  • Work directly with the Product Owner to:
  • Assisting in gathering the requirements for the deployment, implementation and iteration of the in house models.
  • Assist with ensuring the Data science department has the required data for exploration and experimentation.


  • 5+ years of experience in the engineering field and has a track record of making strong architectural decisions.
  • Advanced working knowledge of Apache Spark/Hadoop/Java/Scala
  • Advanced working knowledge of web frameworks and libraries in Python
  • Apache Kafka/Apache Parquet (data storage) knowledge is a big plus
  • Strong knowledge of GCP Products, Kubernetes, and Docker
  • Working knowledge of Node.js/JavaScript
  • Culture of code reviews and collaborating closely with other people 
  • Experience with both relational and non-relational databases 
  • Degree in Computer Science or a related field, or equivalent 
  • Experience with Agile Software Development
  • Self-motivated, detail-oriented, comfortable with ambiguity and able to prioritize work for self and others efficiently 
  • Experience in working with Data Science projects is an asset.
  • Experience in Ad-tech or Mar-tech is an asset.
  • Have at least 5 hours of work overlap with Pacific Time Zone (PST)

How to Apply
Please APPLY by visiting our careers page:

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