Analytics Engineer

Turn Learning Data Into Learning Breakthroughs

At Subject, we're building AI-powered, personalized education at scale. Backed by Owl Ventures, Kleiner Perkins, Latitude Ventures, and more, we serve students across the country with cinematic, video-based learning. But we have a challenge: data is our superpower, and we need more talented, committed, and passionate people helping us build it out further.

We’re looking for an Analytics Engineer to join our growing data and product organization. You’ll sit at the intersection of data, product, and engineering—transforming raw data into accessible, reliable, and actionable insights that guide decision-making across the company.

This role will be foundational in building Subject’s analytics infrastructure, supporting initiatives like:

• Product engagement and learning outcomes measurement
• Operational analytics for school implementations
• Generative AI products (e.g. Subject Spark Homework Helper and SparkTA)
• Data integration across systems like postgres, dbt, Pendo, Looker, and more

You’ll help define what “good data” means at Subject and ensure that stakeholders—from executives to course designers—can make confident, data-informed decisions.

What You'll Build:

Scalable Data Transformation Infrastructure

• Design and optimize dbt models that handle 100M daily events with <5 minute refresh times
• Build modular, tested transformation pipelines that reduce compute costs by 70%
• Create data quality frameworks and governance standards that make our warehouse reliable
• Architect incremental models that process only what's changed

High-Performance Analytics Dashboards

• Build Looker dashboards that load in <3 seconds with millions of rows
• Design Hex notebooks turning hours-long reports into one-click updates
• Create self-service analytics empowering teams to answer their own questions
• Develop real-time monitoring alerting teams to critical student engagement changes

Intelligent Data Models for AI-Powered Learning

• Design dimensional models enabling rapid exploration of learning patterns
• Build feature stores feeding AI systems with clean, timely learning signals
• Create cohort analysis frameworks revealing which interventions work for which students
• Architect data products bridging raw events and business intelligence

Data Infrastructure That Scales

• Write SQL optimized for millisecond response times
• Build Python automation eliminating manual work and catching errors early
• Design orchestration workflows that run reliably and recover gracefully
• Optimize cloud costs while improving performance

The Technical Stack:

• dbt - Transformation layer (50% of your time)
• SQL (PostgreSQL) - Complex analytical queries, performance tuning
• Python - pandas, numpy, matplotlib for analysis and automation
• Hex - Interactive notebooks for reporting
• Looker - Business intelligence and dashboards
• Cloud Data Warehouse - BigQuery

You'll work with billions of learning events, student performance data, video engagement metrics, assessment results, and feedback loops.

What We're Looking For:

Required Experience

• 3-5 years in analytics engineering or data analytics building production systems
• Advanced SQL mastery - Elegant, performant queries. Understanding query plans and optimization
• dbt expertise - Built and maintained dbt projects with 100 models
• Python proficiency - pandas, numpy, automation, and data pipelines
• BI tool experience - Production dashboards in Looker, Tableau, or similar
• Data modeling skills - Dimensional models, normalization tradeoffs, schemas that scale

T

he Mindset We Need

• Performance obsession - Can't stand slow dashboards or inefficient queries
• User empathy - Build for people who need insights, not just technical elegance
• Systems thinking - Optimize the entire data pipeline from source to dashboard
• Ownership mentality - Maintain what you build, not just ship and move on
• Educational curiosity - Genuine interest in learning science and student success
• Collaborative spirit - Explain concepts clearly and elevate team data literacy

Bonus Points

• Education data or student analytics experience
• Data science or ML workflow exposure
• Cloud platform experience (GCP, AWS, Azure)
• Reverse ETL or operational analytics
• Analytics engineering open source contributions

Why This Role Matters:

• Your dashboards inform decisions affecting 5 million students
• Your optimizations save hundreds of engineering hours monthly
• Your data models power AI personalization for each student
• Your work helps teachers understand and improve outcomes

Compensation & Benefits Base Salary: $140K - $180K based on experience Equity: Meaningful ownership that grows with your impact Performance Bonus: Tied to infrastructure improvements and outcomes Health & Wellness: Comprehensive coverage, gym membership, daily meals Location: Los Angeles, CA (in-office preferred)

Ready to Build Education's Data Foundation? This isn't just another analytics role. Define how a category leader uses data, build infrastructure that becomes industry-standard, and improve educational outcomes for millions. Apply now and transform education through data.