Engineering Manager, Data Platform

About Learneo & QuillBot: Learneo is a prominent, virtual-first platform of builder-driven businesses—including Course Hero, CliffsNotes, LitCharts, Scribbr, and QuillBot—all united around a shared mission of supercharging productivity and learning loops for everyone. As an innovative corporate collective, Learneo scales high-growth digital businesses built and run by visionary entrepreneurs. This specific engineering track powers QuillBot, an industry-leading AI writing platform trusted by over 60M+ users globally to streamline and improve their communication capabilities.

Position Overview

We are seeking a deeply technical, product-minded Engineering Manager to lead, scale, and modernize the core Data Platform infrastructure powering QuillBot’s global product intelligence, live experimentation, usage metering, and lifecycle marketing systems. In this critical leadership seat, you will act as both an architectural guide and a strategic driver, running our distributed data ecosystem as an internal product to maximize value for cross-functional builders. Managing a dedicated team of platform engineers, you will choose technologies, manage data quality baselines, optimize cloud spending ratios, and build scalable data pipelines designed to feed Generative AI model training tracks.

Key Responsibilities

• Data Platform Architecture Evolution: Own the long-term technical architecture and scaling operations of distributed data engines, managing both large-scale real-time streaming and high-volume batch processing.
• Analytical Systems Design: Design and deploy robust internal frameworks for continuous product experimentation, system usage metering, and real-time event tracking loops.
• High-Performing Team Leadership: Recruit, mentor, and guide a high-performing squad of data and platform engineers, fostering a culture of ownership, rapid innovation, and clear career pathing.
• Platform-as-a-Product Management: Enhance the absolute developer experience and daily tool usability for internal data stakeholders, tracking platform KPIs like adoption rates, latency, and system uptime.
• Cross-Functional AI Collaboration: Partner closely alongside Product, Growth, Marketing, and AI Research squads to translate business requirements into scalable ETL/ELT pipelines and support data sets for machine learning models.
• Performance & Cloud Cost Optimization: Evaluate infrastructure spending across public clouds, systematically optimizing compute resources and pipeline execution behaviors to maximize ROI.

Required Skills & Qualifications

• 7+ years of verified professional software or data engineering history, containing at least 2+ years of explicit engineering management experience.
• Deep technical depth and architectural judgment scaling high-capacity data platforms or distributed big-data systems.
• Hands-on programming familiarity working inside backend ecosystems, specifically including Node.js and JavaScript environments.
• Production-grade experience managing massive data routing architectures, using engines like Apache Spark, streaming pipelines, and ETL/ELT tools.
• Demonstrated capability to make clear technical trade-offs and lead large-scale infrastructure initiatives across major public clouds (AWS, GCP, or Azure).
• Outstanding cross-functional communication mechanics, optimized to align technical software systems with broad business milestones.

Preferred Strategic Indicators (Nice to Have)

• Prior experience managing high-availability data infrastructure supporting consumer applications at millions of users scale.
• Familiarity running specialized machine learning data frameworks, growth analytics, or customized experimentation engines.
• Basic familiarity with frontend technologies like React.js to help evaluate internal visualization tools or administrative dashboards.

What We Offer

• The exceptional technical runway to govern the data platform powering a global AI suite used by over 60 million active people.
• Highly competitive compensation package including a performance-based annual bonus and market-calibrated base pay tracking.
• Comprehensive health insurance, life coverage, and accidental insurance protections.
• Generous personal leave allocations, including specialized flexible vacation frameworks, maternity/parental leave, and menstrual leave options.
• Profound work-from-home remote independence supported by new-hire technology stipends and annual WFH allowances.
• Premium, unrestricted corporate access to the entire QuillBot product suite alongside continuous professional development and training reimbursements.