Define and execute the long-term vision for Kiddom’s data platform supporting analytics, AI/ML, and product intelligence.
Architect scalable batch and real-time data pipelines powering personalization, reporting, and learning insights.
Establish best practices for data modeling, data quality, lineage, and observability across the organization.
Guide evolution of data infrastructure across cloud-native environments and distributed systems.
Ensure data systems meet performance, scalability, reliability, and compliance requirements as product usage grows.
Partner with AI/ML teams to enable feature stores, experimentation workflows, and model training pipelines.
Support delivery of AI-powered product capabilities through reliable, well-modeled datasets.
Collaborate with Product and Engineering leaders to integrate data seamlessly into user experiences and decision systems.
Build, mentor, and scale a world-class data engineering organization.
Establish clear technical standards, career growth paths, and operational excellence practices.
Foster a culture of ownership, collaboration, and continuous improvement.
Provide technical guidance while empowering engineers to lead initiatives.
Work closely with Product, Curriculum, Analytics, Customer Success, and GTM teams to translate business needs into scalable data solutions.
Support company planning through data strategy aligned with customer adoption cycles and business priorities.
Drive alignment between platform engineering, infrastructure, and analytics initiatives.
Requirements
10+ years of experience in data engineering, backend engineering, or distributed systems.
4+ years leading or managing high-performing engineering teams.
Passion for attracting and growing top notch talent.
Proven experience designing and operating large-scale data platforms in production environments.
Strong expertise in SQL and programming languages such as Python or Go.
Experience with modern cloud data ecosystems (AWS preferred), including services such as: S3, EKS/ECS Data warehousing platforms (Snowflake or similar), streaming and real-time data systems.
Deep understanding of data modeling, pipeline orchestration, and analytics architecture.
Experience supporting AI/ML workflows and data products.
Ability to balance strategic leadership with hands-on technical depth.
Tech Stack
AWS
Cloud
Distributed Systems
Python
SQL
Go
Benefits
Competitive salary
Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year.
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State.