POSITION DETAILS

  • Own the heart and soul of our technology: the collection and transformation of tons of enterprise data into actionable data driven product insights
  • You will be primarily responsible for:
    • Identifying, pulling, structuring, and storing signal rich data from our enterprise customers
    • Interpreting this data and delivering data driven product insights via API to our user-facing mobile and web applications
  • You’ll need to be able to do these things well to succeed at this job
    • Design and build efficient and reliable client applications to interact with 3rd party APIs
    • Design and build efficient and reliable data ingestion, normalization, and refreshing systems from scratch
    • Design flexible and scalable relational and object models and operate our system of record
    • Design and build a scalable (enables rapid product iteration) backend platform that takes full advantage of our data to power impactful data driven products, including our anomaly detection system
    • Design and build efficient, reliable, and clean internal APIs
    • Effectively and intelligently scale our platform and remain flexible as we increase the number of data sources, insights, users, and organizations we support
    • Operate efficiently and effectively in our existing Java, PostgreSQL, and AWS stack (it’s OK if you need to ramp on these specific technologies, as long as you have the experience and interest to effectively do so)
    • Willingness and ability to effectively jump into any part of the application to deliver end to end features and fix issues
    • Operate efficiently and effectively in a pre-product market fit environment by pragmatically balancing time to market with scalability
    • Be excited about working every day in our San Francisco office, and believe in the value of teams working most of the time together and in person
  • While none of these are required for the role, you’ll be able to own even more if you can do some of these things well (or are effective at learning them!)
    • Data product management - Investigate inefficiencies and identify data product enhancements to incrementally improve our existing product features (from iterating the way we use existing data sources to identifying new data sources)
    • Team lead - Effectively provide architectural guidance, thought leaderships, and engineering mentorship for a team of engineers
  • We would be open and excited if you also had these skills or interests
    • Data analytics - Use statistical analysis to identify correlations between user behavior and outcomes
    • Data science - Identify and extract new “ah ha” product insights and features from our large corpus of data
    • Organizational design - Thoughtfully help us design and evolve our culture and process as we grow
    • People management - Effectively hire, manage, and scale a data engineering organization

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