Analytics Engineer / Data Engineer for Kiddom
About Kiddom
Kiddom is a groundbreaking educational platform that promotes student equity and growth by uniting high-quality instructional materials with dynamic digital learning. Through unparalleled curriculum management functionality, Kiddom empowers schools and districts to take ownership of their curriculum – resulting in learning experiences tailored to meet the unique needs and goals of local communities. Kiddom’s high-quality curriculum is layered with robust teacher and leader data insights to drive the continuous improvement of instructional decisions, school/district programming, and professional learning.
About the Role
The Data Analytics Engineer will build the data products, pipelines, and guardrails that make product insight accessible and actionable across Kiddom. This role directly supports internal teams by developing reliable product insights data, automating pipeline design and quality controls, and bringing in third-party data sources that are not available to the organization today.
You will serve as the primary analytics engineering partner to our Data Science & operations team, a peer who co-owns the data layer that makes their work possible. You will own Kiddom’s Snowflake data warehouse, build and maintain ELT pipelines that centralize data from across our SaaS stack, and bring observability and rigor to infrastructure that is scaling fast alongside our AI and analytics initiatives.
Looking for someone who has operated as a true DE partner to technical and non-technical teams before and has the maturity to know what that relationship looks like when it’s working well and what questions to ask to gather the proper requirements.
What you’ll do
- Own and optimize Kiddom’s data stack: Including data warehouse / modeling / cost controls / access patterns
- Build and maintain ELT pipelines ingesting from SaaS sources (Salesforce, HubSpot, NetSuite, Ramp) using Airbyte or equivalent
- Partner with Data Science to design fact/dimension models, data marts, and reusable datasets supporting experimentation and reporting
- Build observability and data quality monitoring into pipelines by default (alerting, thresholds, and SLA tracking)
- Extend and document Kiddom’s dbt project, bringing modeling rigor and ensuring a true partnership on warehouse architecture
- Define the service model that distinguishes maintained pipelines from one-off pulls, and advocate for it with stakeholders
What we’re looking for
- 4+ years of data engineering experience; strong SQL and comfortable with Python — SQL fluency is a hard requirement, not a preference
- Snowflake experience beyond querying: warehouse administration, cost controls, and data sharing
- Fact/dimension modeling depth: you’ve built it for teams who depend on it, not just learned about it
- Experience ingesting from SaaS APIs using modern ELT tooling (Airbyte, Fivetran, or equivalent)
- Proactive communicator – Over-communicates status and blockers unprompted; knows how to say no with a path forward
- Startup experience — comfortable building structure where none exists, operating without a fully defined roadmap
- 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
- BS or MS in Computer Science or a related field
- Advanced English proficiency (B2–C1 or higher)
Nice to have
- dbt proficiency: can extend, refactor, and document an existing dbt project independently
- CDC (Change Data Capture) experience – Know the difference and how to setup a SCD Type 1 vs SCD Type 2
- Multimedia pipeline experience — you have built pipelines that ingest and process audio, video, or image data at scale, including object storage patterns, format normalization, and metadata enrichment
- Experience using AI-assisted or agentic development workflows for data engineering.
Benefits
- Collaborative and innovative work environment.
- Flex PTO for any reason, including sick days (no specified limits), flexible work schedule.
- Personal laptop.
- Health and wellness package.
- Budget for English lessons.
As this is an English-speaking role, we kindly ask that all applications be submitted with a CV in English.
