Staff Data Engineer, Analytics

1 Week ago • 5 Years + • Data Analyst

Job Summary

Job Description

As a Staff Data Engineer, you'll work on diverse initiatives spanning data engineering and data science to enhance Character's product through analytics. You'll partner with Data Platform and Data Science teams to optimize warehouse design, evolve product analytics systems, expand product data use cases, and foster a data-driven culture. Key responsibilities include designing and maintaining a robust data warehousing design for reliable reporting, owning the core company data pipeline, evolving data models, implementing data quality tracking, and improving pipeline performance. The ideal candidate has 5+ years of experience in data engineering, preferably in a consumer-facing tech company, and proven expertise with BigQuery, Spark, DBT, Airflow, unstructured data processing, event telemetry systems, and product experimentation platforms.
Must have:
  • 5+ years data engineering experience
  • BigQuery, Spark, DBT, Airflow expertise
  • Unstructured data processing
  • Event telemetry system experience
  • Strong Python and SQL skills

Job Details

Responsibilities:

As Staff Data Engineer, you will work on a diverse set of initiatives spanning the data engineering and data science domains to help Character grow its product through analytical excellence. 

You will partner with our Data Platform and Data Science teams to optimize warehouse design and performance, evolve critical product analytics systems, enable and expand use cases of product data and help develop a world-class data culture. Your initial focus will be on these key areas:

  1. Enable product team insights: Design, implement, and maintain a robust data warehousing design for consistent and reliable reporting and ease of data exploration as we continue to better understand our users

  2. Own the core company data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Character

  3. Evolve data model and data schema based on business and engineering needs, help character adopt best practices

  4. Implement and adopt systems tracking data quality and consistency, improve pipeline performance and reliability 

Requirements:

  • 5+ years experience in data engineering, preferred within a consumer-facing technology company (chat, social media, or UGC)

  • Experience building data warehousing and pipelines with BigQuery, Spark, DBT and Airflow

  • Experience with processing and transforming unstructured data sources.

  • Experience modeling and scaling event telemetry systems for analytical use-cases

  • Experience implementing and supporting product experimentation data platforms

  • Proven track record of cross-functional execution and collaboration

  • Strong Python and SQL experience

    Locations:

  • NYC Preferred, SF Bay Area OK

About Character.AI

Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures.


In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach.


Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!

At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.

Compensation Range: $150K - $250K

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About The Company

Character is one of the world's leading personal AI platforms. Founded in 2021 by AI pioneers Noam Shazeer and Daniel De Freitas, Character is a full-stack AI company with a globally scaled direct-to-consumer platform. 

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