Summary

Glide is looking for a data science engineer to define our data infrastructure and deliver insights to our sales, marketing, and product teams.

You will be responsible for defining and maintaining our end-to-end data strategy, from collection, to modeling, to visualization and communication to the entire company. The ideal candidate is an experienced data architect who enjoys optimizing existing data systems for clarity and correctness, building new data systems from the ground up, and is eager to empower our sales, marketing, and product teams with data-driven insights.

You must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to answer critical questions about our business.

By ‘data science engineer’, we mean a hybrid data scientist with some data engineering chops–you will be our first full-time data hire, so you will need to build upon our data engineering foundation.

You will:

• Work with BigQuery, Firestore, Postgres, Stripe, Mixpanel, and Hubspot.

• Maintain our dbt models and workflows, iterate them under source control, and test them for correctness.

• Collaborate with sales, marketing, engineering, and growth teams to build dashboards that answer our most urgent questions.

You should have:

• Experience as a data engineer at a high-growth startup

• Technical expertise with data models, data collection, and segmentation techniques

• Expert knowledge of SQL and BigQuery

• Familiarity with the GCP data suite (DataProc, Dataflow, Data Studio, BigQuery)
• Extra points for Kafka, PubSub or Kinesis. Debezium and/or other streaming ETL.

• Knowledge of ETL tools like Airflow/AirByte/FiveTran

• An eye for cogent data visualization

Definitely mention if you have:

• A degree in Math or CS

• Any open source work you’d like to show off

• Experience with Retool

• Experience with TypeScript