The Data Analytics Engineer’s mission is developing Alice’s data and machine learning infrastructure.
 
In this role, you’ll help develop the pipelines, warehouse, and models that inform our data-driven decisions. You’ll also work on ML systems to provide our customers the highest quality service. As an early member of the Data Platform team, you’ll help shape our roadmap and build the culture that gets us there. We value critical thinkers and independent operators who get the job done. If you’re excited about DataOps, MLOps, and building with the latest and greatest cloud tech, this role might be for you!

 

Data Analytics Engineers help us meet these needs:

  • Data modeling in multiple systems
  • Engineering our machine learning system and running ML experiments
  • Refining our data platform architecture
  • Building and orchestrating data pipelines
  • Supporting the Alice team and our users by building self-serve data views.
  • Balancing scalability, reliability, maintainability, and delivery speed while solving complex challenges.
  • Developing our DataOps and MLOps practices

Data Analytics Engineer Standards:

  • 3-5 years of experience working as a Data Engineer
  • Strong SQL and Python skills
  • Experience building on cloud data warehouses like BigQuery, Snowflake or Redshift
  • Experience with distributed data processing using tools like Spark, Presto, Beam, etc.
  • Experience with orchestration tools like Airflow, Dagster, or Luigi
  • A strong sense of ownership and a strong desire to help others succeed
  • Experience with ML modeling and/or MLOps
  • Experience with streaming analytics tools like Segment and MixPanel
  • Experience with build for GDPR or CCPA compliance in large scale data systems
  • Experience with Docker, Kubernetes, and/or Ruby on Rails

You’re the right fit for us if:

  • You think about reliability, scalability, and maintainability
  • You love a challenge and remain upbeat and positive while taking them on
  • You see data analytics as a critical service to the business
  • You either have experience with or are interested in building machine learning systems
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