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Streaming Architecture with Kafka, Materialize, dbt, and Tecton

Posted Jul 14
# Data engineering
# Feature Stores
# Production Use Case
# Systems and Architecture
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SPEAKER
Emily Hawkins
Emily Hawkins
Emily Hawkins
Data Infrastructure Lead @ Drizly

Emily Hawkins is the Data Infrastructure Lead at Drizly. She is based in Boston, MA. Emily has a Master of Science in Business Analytics from Bentley University. She has been working in data for the past 6 years and is heavily involved in the modern data stack community, working with tools like Snowflake, Dagster, Fivetran, dbt, and Looker.

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Emily Hawkins is the Data Infrastructure Lead at Drizly. She is based in Boston, MA. Emily has a Master of Science in Business Analytics from Bentley University. She has been working in data for the past 6 years and is heavily involved in the modern data stack community, working with tools like Snowflake, Dagster, Fivetran, dbt, and Looker.

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SUMMARY

Drizly is building out our Data Science stack and streaming infrastructure to match the success we've had with the modern data stack on BI. We are currently standing up our architecture using Kafka, Materialize, and dbt. We are planning on adding Tecton into this stack as our feature store for Data Science. We can show our current plans for infrastructure, talk about the pros of this stack, and touch on how this opens up future possibilities with Tecton as our feature store.

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Posted Jun 01 | Views 66
# Data engineering
# Open Source