Job description

About Kiddom Kiddom is transforming K–12 education by bringing high-quality curriculum, instructional tools, and student analytics together in one coherent system. We are building Learning Intelligence Technology (LIT), a new category that gives educators the infrastructure to plan, teach, assess, and respond to student needs. With Kiddom, educators spend less time managing administrative burden and more time delivering meaningful student instruction. Kiddom helps schools and districts deliver more equitable, effective, and adaptive learning experiences. We're looking for a Senior Data Engineer to join Kiddom's Content & AI Systems team, building the data layer that powers next-generation AI-assisted curriculum authoring and content delivery. You'll own the pipelines, schemas, and validation frameworks that turn messy, domain-specific curriculum content into structured, AI-ready data products, working closely with Instructional Designers, AI engineers, and the Content Agents team. This role suits an engineer who's comfortable in a non-traditional data engineering space and energized by defining data requirements and infrastructure from the ground up. You will: - Design and own the schema and data models representing Kiddom’s curriculum content (lessons, activities, standards alignments) for downstream use - Build ingestion pipelines that process content from varied, inconsistent source formats — XML, JSON, PDF-derived, and API-delivered - Develop Python-based parsers, transformers, and validation scripts that enforce schema conformance and content quality at scale - Collaborate directly with Instructional Designers and product teams to translate content authoring workflows into data engineering requirements - Build and maintain embedding and vector database pipelines that feed Kiddom’s AI-powered content features as they scale - Work in Git-based workflows — treating data artifacts with the same rigor as software: versioned, reviewed, and documented What we're looking for: - 4+ years of data engineering experience with strong Python skills — you’ve written parsers, validators, and transformation scripts for real-world messy data - Schema design instincts — you think carefully about how data should be structured for downstream use, not just how to move it - Data quality mindset — you build validation and completeness checks in from the start, not as an afterthought - Cross-functional collaborator — comfortable working with non-engineers to define requirements and translate domain knowledge into data structures - Provisioning and monitoring of infrastructure for data systems, familiarity with IaC tools such as Terraform and Terragrunt - The data system operates, ECS, EKS clusters, provision lambdas and S3 buckets - Bachelor’s or Master’s degree in CS or equivalent work experience Nice to Have: - Background in education, curriculum design, or ed-tech — understanding how instructional content is authored and structured is a genuine differentiator - Experience with vector databases (Pinecone, Weaviate, pgvector) or embedding pipeline tooling - Familiarity with agentic AI patterns or Model Context Protocol (MCP) What we offer - Full time permanent employees are eligible for the following benefits from their first day of employment: - Competitive salary - Meaningful equity - Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance - 401k plan - 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. - Commuter and FSA plans Equal Employment Opportunity Policy Kiddom is committed to providing equal employment opportunities to all employees and applicants without regard to race, religion, color, gender, sexual orientation, transgender status, national origin, citizenship status, uniform service member status, pregnancy, age, genetic information, disability, or any other protected status in accordance with all applicable federal, state, and local laws.

Requirements

Must-haves

Design and own the schema and data models representing Kiddom’s curriculum content (lessons, activities, standards alignments) for downstream use
Build ingestion pipelines that process content from varied, inconsistent source formats — XML, JSON, PDF-derived, and API-delivered
Develop Python-based parsers, transformers, and validation scripts that enforce schema conformance and content quality at scale
Collaborate directly with Instructional Designers and product teams to translate content authoring workflows into data engineering requirements
Build and maintain embedding and vector database pipelines that feed Kiddom’s AI-powered content features as they scale
Work in Git-based workflows — treating data artifacts with the same rigor as software: versioned, reviewed, and documented
4+ years of data engineering experience with strong Python skills — you’ve written parsers, validators, and transformation scripts for real-world messy data
Schema design instincts — you think carefully about how data should be structured for downstream use, not just how to move it
Data quality mindset — you build validation and completeness checks in from the start, not as an afterthought
Cross-functional collaborator — comfortable working with non-engineers to define requirements and translate domain knowledge into data structures
Provisioning and monitoring of infrastructure for data systems, familiarity with IaC tools such as Terraform and Terragrunt
The data system operates, ECS, EKS clusters, provision lambdas and S3 buckets
Bachelor’s or Master’s degree in CS or equivalent work experience

Nice-to-haves

Background in education, curriculum design, or ed-tech — understanding how instructional content is authored and structured is a genuine differentiator
Experience with vector databases (Pinecone, Weaviate, pgvector) or embedding pipeline tooling
Familiarity with agentic AI patterns or Model Context Protocol (MCP)

Application prep

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Keywords to mirror

aiapipython

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401k