Principal Data Engineer (Remote)


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Upgrade Inc.
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Posted 1 month ago

Upgrade is a fintech unicorn backed by a top 10 global bank and other leading fintech investors. Founded in 2017, Upgrade has already delivered $4 billion in consumer credit and achieved $125 million in annual revenue run rate and cash profitability.
Upgrade is building a neobank offering exceptional value to mainstream consumers, including affordable and responsible credit through cards and loans. In 4 short years 10 million people have already applied for an Upgrade Card or loan.
Upgrade has been named a “Best Place to Work in the Bay Area” by the San Francisco Business Times and Silicon Valley Business Journal 3 years in a row, and received “Best Company for Women” and “Best Company for Diversity” awards from Comparably.
We are looking for new team members who get excited about designing and implementing new and better products to join a team of over 400 talented and passionate professionals. Come join us if you like to tackle big problems and make a meaningful difference in people's lives.
This is a remote position based in Canada.

What you will do:

  • Quickly gain a deep understanding of the business and how data flows through the organization.
  • Collaborate with Business Intelligence, Engineering, Product, Decision Sciences and TechOps teams to understand our source data and help build a world class data warehouse in the cloud that will act as the single source of truth for all information in the organization.
  • Build and own awesome scalable data pipelines to enrich the data warehouse.
  • Proactively develop solutions for new product initiatives or data needs.

What you will get:

  • An opportunity to be a part of a young organization where what you build will be of great meaningful impact and will pave the way for our future success and yours too.
  • A highly open, collaborative and supportive team environment that will encourage your crazy but brilliant ideas and respect your decisions. 
  • Help and support in creating goals that drive you, take on projects that excite you and learn new things everyday.

What you have/are:

  • 5+ years of data engineering experience in designing, building, maintaining and scheduling efficient, scalable and reliable batch and real-time data pipelines using SQL and general data processing language such as Python or Scala.
  • Good understanding of query tuning and optimization with a knowledge of database internals.
  • Understanding of overall system architecture, scalability, reliability, and performance in a large data warehousing environment such as Redshift, Snowflake, Teradata, etc. and ensure overall efficiency.
  • Experience designing and understanding data warehouse performance benchmarks for large scale data analytics.
  • Strong knowledge of source code version control with Git.
  • Highly collaborative with Business Intelligence Analysts, Product teams and Data Scientists with great social skills and high levels of empathy.
  • Worked in a fast paced environment being scrappy when needed.
  • You hate doing the same task more than once and always think about automation.

Bonus points for:

  • Experience with cloud technologies.
  • Experience with Docker and Kubernetes.
  • Experience with real time data processing using Kafka, RabbitMQ, Kinesis or SQS.
  • Experience with financial data and its secure storage and retrieval.
  • Experience with Python frameworks such as Flask, SQLAlchemy, Django.


  • Competitive salary and stock option plan. 
  • 100% paid coverage of medical, dental and vision insurance. 
  • Unlimited vacation. 
  • Learning stipend for personal growth and development. 
  • Paid parental leave.  

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Job tags: Business Intelligence Data Analytics Data Warehousing Engineering Kafka Kubernetes Python Redshift Scala SQL
Job region(s): North America Remote/Anywhere
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