About the job
Join Us in Transforming the Creator Economy with AI
Fanvue is rapidly emerging as one of the leading platforms for creator monetization on a global scale. Our AI-driven, creator-centric platform empowers creators to connect with their audiences, engage meaningfully, and generate income directly at scale. Following our successful Series A funding, Fanvue has achieved over $100M in annual recurring revenue, with impressive triple-digit growth year-over-year, supporting countless creators and millions of fans around the world.
As we continue to expand, the significance of data within our organization is becoming increasingly vital across various functions including product development, growth strategies, finance, and risk management. This position is pivotal in establishing a robust data foundation that the entire company can rely on, facilitating quicker decision-making, sophisticated analytics, and scalable machine learning capabilities.
The Role
We are seeking a Senior Data Engineer to take charge of and enhance Fanvue’s essential data infrastructure.
This is a crucial, high-impact role where you will stabilize data ingestion processes, enhance observability and governance, minimize manual tasks, and enable advanced analytics and machine learning workloads. Your contributions will be foundational in helping Fanvue thrive as a genuinely data-driven organization.
Responsibilities
Oversee and stabilize end-to-end data ingestion pipelines, including Change Data Capture (CDC) ingestion using Amazon DMS
Address schema drift challenges and automate column ingestion to eliminate manual re-sync efforts
Develop production-grade observability for data pipelines, dbt runs, and Athena performance
Set up monitoring and alerting frameworks to proactively identify data quality issues or pipeline failures
Enhance CI/CD workflows for data transformations, aiming to reduce PR build times and deployment complexities
Design and implement reusable ingestion frameworks for swift onboarding of new data sources
Establish robust data governance protocols, including dbt tests in production and scheduled full-refresh pipelines
Facilitate advanced analytics and ML infrastructure, including AWS SageMaker integration and on-demand analytics environments
Implement fine-grained access controls (RBAC) to safeguard PII and sensitive data as the company scales
Manage Infrastructure as Code for the data platform utilizing AWS CDK

