Posted 1mo ago

Engineering Manager, Data Platform

@ Multi Media LLC
United States
$181k-$237k/yrRemoteFull Time
Responsibilities:Define strategy, Establish standards, Lead team
Requirements Summary:2-5 years people management; 7+ years data engineering/backend/platform engineering; experience with high-volume data; DBT; data modernization; ML/personalization; stakeholder management.
Technical Tools Mentioned:DBT, DataWarehouse, Lakehouse, Orchestration, CI/CD, ETL, Cloud
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Job Description

About us: Multi Media LLC is a leader in digital innovation, focusing on creating modern products for the content creator community. Our main platform, Chaturbate, is a key player in the adult entertainment industry, bringing billions of people together worldwide. We aim to make Chaturbate the best place for users and creators to interact and connect, offering a safe, creative, and engaging space for everyone.

We’re looking for an Engineering Manager to lead our data platform team and evolve our data ecosystem to reliably support personalization, experimentation, and analytics at scale. In this role, you will actively shape the mission and vision of the modern data platform and partner closely with Engineering, Product, Data Science, Machine Learning, Analytics, and Security to balance incoming business needs with long-term platform investments.

As a people manager, you’ll oversee the team of data and analytics engineers, ensuring their professional growth, providing technical guidance, and fostering a culture of ownership, accountability, and high engineering standards.


What you’ll do in particular: 

  • Own and define the long-term strategy and roadmap for our Data Platform, ensuring it supports personalization, experimentation, and analytics at scale.
  • Establish and uphold standards for data quality, governance, reliability, and platform performance.
  • Lead, mentor, and grow a high-performing team of data and analytics engineers.
  • Drive clear prioritization across stakeholder requests while protecting foundational platform investments.
  • Work closely with Product, ML, and Analytics teams to ensure the platform delivers trusted, well-defined, and accessible data that meets their evolving use cases.
  • Continuously evaluate our data stack and infrastructure, recommending concrete improvements to architecture, tooling, and workflows to keep the platform scalable, reliable, and cost-efficient.