Quillbot~20d ago

Engineering Manager, Data Platform

IndiaRemotemid

EngineeringOtherDevOps & InfrastructureData EngineeringManagementEngineering ManagerPlatform

0 views0 saves0 applied

Apply Now

Quick Summary

Overview

About Us QuillBot was founded in 2017 with a mission to help students and professionals strengthen their writing. Today, we help over 56 million people around the world create great things.

Technical Tools

EngineeringOtherDevOps & InfrastructureData EngineeringManagementEngineering ManagerPlatform

Responsibilities

~1 min read

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.

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.

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.

Improve the developer experience and usability of the data platform for internal teams.
Define and track platform KPIs such as adoption, reliability, and performance.

Optimize infrastructure for cost efficiency and performance at scale.
Continuously evaluate tools, technologies, and processes to improve ROI.

Supporting AI research with data, both for training and capabilities.

Requirements

~1 min read

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 (AWS/GCP/Azure) and modern data stack tools.
Proven ability to make architectural trade-offs and lead large technical initiatives.
Strong communication skills with experience working cross-functionally across business teams

Nice to Have

~1 min read

Experience supporting AI/ML, experimentation platforms, or growth analytics.
Familiarity with frontend technologies like React.js for building internal tools or dashboards.
Experience handling data systems at consumer scale (millions of users).