Data Engineer/Lead - Job Description
About the company:
EasyKnock is a real estate technology startup disrupting the finance and real estate industries. By changing how homeownership is approached, we can help the millions of Americans trying to access their home equity. Where lenders see numbers, we see people. Our first product, Sell and Stay, is a sale-leaseback with an option to repurchase. We are the first company in the United States offering such a revolutionary and flexible program that puts consumers first. We’ve invented something so simple and yet so powerful you’ll wonder why no one came up with it before. Closing our Series A, we are poised to expand to new markets, channels and programs!
About the opportunity:
EasyKnock is building a data science team to rapidly scale! The team will be gathering and processing data on homes, economic conditions, and geographies to better understand our customers and to assess risk.
The lead data engineer will responsible for the data processes at EasyKnock, loading data from our CRM, Marketing platforms, and 3rd party sources into a normalized schema for the data scientists to process.
- 3+ years of hands-on experience designing and building large scale data warehouse solutions across the entire data lifecycle, from raw data to powerful insights and analytics.
- Experience in working with and optimizing existing data ingestion, cleansing, transformation, integration, and validation flows and helping to move them into production.
- Proficient in Scala and Spark.
- Experience with cloud computing platforms AWS (S3, EC2, Lambda, Redshift, etc)
- At least 1 year of experience functioning as a lead or senior resource on a team.
- Experience in productionizing machine-learning models (e.g. AWS Sagemaker)
- Knowledge about agile software processes
- Experience with Snowflake