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Analytics Engineer

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Salary

$108,000 USD and $146,000 USD or $95,000 CAD and $129,000 CAD

Location

Remote within Canada and the US

As an Analytics Engineer, you will be a member of the Data & Analytics Engineering team, building the foundation to scale analytics across our organization. You will collaborate with key stakeholders in Analytics, Engineering, Product, Go To Market/Sales, Marketing, Finance and other business areas to build scalable solutions to transform data into key metrics, reporting and insights. You will be responsible for ensuring teams have access to reliable, accurate metrics that can scale with our company’s growth.

What we're looking for:

  • Minimum of 2+ years of experience as a Analytics Engineer, Data Engineer or in a similar role with a proven track record in shipping canonical datasets
  • Minimum of 2+ years technical experience leveraging dbt and SQL for data transformation
  • Minimum of 2+ years building LookML models in Looker (or equivalent experience in other Business Intelligence tools with a semantic layer)
  • Proficiency in at least one functional/OOP language such as Python or R
  • Proficiency in version control (e.g., Git) and command-line tools
  • Familiarity with leveraging distributed data stores (e.g. S3, Trino, Hive, Spark)
  • Experience building multi-step ETL jobs coupled with orchestrating workflows (e.g. Airflow, Dagster)
  • Experience in writing unit tests to validate data products and version control (e.g. GitHub, Stash)
  • Experience solving ambiguous problem statements in an early stage environment

What you can expect:

  • Collaborate with team members to collect business requirements, define successful analytics outcomes, and design & build data models
  • Full stack analytics engineering development, building models to consume, transform, and expose data to stakeholders and production systems
  • Drive a culture of experimental design, testing agenda, and best practices
  • Contribute to the culture of 1Password’s Data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way
  • Collaborate with Analytics, Business, Product, Engineering and Data Infra teams to develop roadmaps and measure success
  • Work closely with Data Engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action

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