Senior Data Engineer

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

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)