Open Opportunity

Data Engineer


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As a 7-year-old technology company in the real estate space, our vision is to make buying and selling a home a truly delightful experience. With a powerful flywheel-driven business model, our culture is built upon helping people uncover their biggest strengths and using them to the fullest extent possible. We’re also delightfully weird, which means that we take pride in being authentically ourselves. If this sounds like a place you’d find interesting – keep reading!

Are you a business and goal-minded Data Engineer? Our Data Science team is looking for a person to lead the technical execution of high-impact company projects, as well as scale our data science practice by providing a strong integration point between the Data Science team’s work and the rest of the company’s tech stack. A key part of this role will be mobilizing data to stakeholders in engineering, product, customer success, sales and marketing in order to accelerate the growth of our business.

We have adopted a permanent “work from anywhere” culture – meaning you have complete freedom to decide where you want to work (at home, at a coffee shop, co-working space, in our office in Orange, California once it reopens, or traveling the country in a vintage RV). As long as you’ve got a strong WiFi signal, you’re good. Therefore, we are open to candidates in any location in the US.

What you’ll do:

You’ll work on (major) special projects needed within product development, engineering, and marketing to ensure there is a heavy business intelligence layer in every decision we make as we continue to grow. Ultimately, we’re looking for a capable data developer who can work cross-departmentally.

Knowledge must-haves:

  • Python (including packages such as numpy, pandas, sklearn, matplotlib, tensorflow or pytorch, Plotly Dash, dask, etc.)
  • Git
  • AWS Cloud Services (including Lambda, EC2, S3, ElasticSearch, Sagemaker, DynamoDB, AWS RDS)
  • SQL databases (like MySQL) and nSQL databases (like MongoDB) as well as other structured and unstructured data sources

Knowledge nice-to-haves:

  • R: tidyverse, data.table, R Shiny, caret, etc.
  • Spark, PySpark, or SparklyR
  • Snowflake, Looker, or similar tools
  • Developing packages/libraries for Python and/or R
  • Productionalizing ML models in AWS
  • Javascript, HTML, CSS
  • Salesforce
  • Analytical tools and tag implementation

Specifically, we’re also looking for:

  • Independence: You’ll be the only Data Engineer on our data science team (for now), so you’ll often have to operate without direct guidance and must have the confidence to do so. Our team also operates without a project manager, so organizational and time management skills are key.
  • Easy to work with: You’ll be working cross-functionally with a lot of different players – primarily engineering but also product, customer success, sales, and marketing. You must be a strong communicator who is patient with people who don’t understand things the way you do.
  • Speed: You are not a perfectionist, because speed matters. You’ll have to take data tables and stand them up quickly so that our team can access the information and use it to accelerate growth quickly.

Because this is a new role in our data science team, we are looking for someone with about 5 (or more) years of experience. This role reports to our VP of Data Science and Analytics