Engineering Manager, Data Platform

Role Overview

We are looking for an experienced Engineering Manager—Data Platform to lead and scale Quillbot’s data infrastructure powering our product, AI, and growth initiatives. With over 60M+ users, our data platform is critical to enabling product intelligence, experimentation, usage metering, and lifecycle marketing.

This role is both technical and strategic—you will drive architectural decisions, build high-performing systems, and lead a team of engineers to deliver a reliable, scalable, and cost-efficient data platform. You will also treat the platform as an internal product, ensuring usability and value for cross-functional stakeholders.

Responsibilities

• Technical Leadership & Architecture
  • Own the architecture and evolution of the data platform to support large-scale, real-time, and batch data processing.
  • Design systems for analytics, experimentation, event tracking, and usage metering.
  • Ensure high standards of scalability, reliability, performance, and data quality.
  • Drive best practices in data engineering, system design, and observability.
• Team Leadership & Development
  • Build, mentor, and lead a high-performing team of data and platform engineers.
  • Foster a culture of ownership, innovation, and continuous improvement.
  • Provide technical guidance, career development, and performance management.
• Cross-functional Collaboration
  • Partner closely with Product, AI, Growth, and Marketing teams to understand data needs and translate them into scalable solutions.
  • Enable data-driven decision-making across the organization.
• Platform as a Product
  • Improve the developer experience and usability of the data platform for internal teams.
  • Define and track platform KPIs such as adoption, reliability, and performance.
• Performance & Cost Optimization
  • Optimize infrastructure for cost efficiency and performance at scale.
  • Continuously evaluate tools, technologies, and processes to improve ROI.
• Gen AI and Automation
  • Supporting AI research with data, both for training and capabilities.

Qualifications

• 7+ years of experience in software/data engineering, with 2+ years in engineering management.
• Strong technical depth + architecture judgment.
• Strong experience building and scaling data platforms or distributed systems.
• Hands-on experience with backend technologies like Node.js and JavaScript ecosystems.
• Real experience with systems like Spark, streaming, pipelines.
• Solid understanding of data pipelines, ETL/ELT processes, and analytics systems.
• Experience with cloud platforms.