Senior Data Engineer

Age of Learning
Hybrid

About The Position

As a Senior Data Engineer on the Data and Analytics team, you set the architectural direction for our data platform and own the trustworthiness of the data layer the company relies on. You partner closely with data analysts, product managers, designers, and production engineers, translating their needs into durable systems, mentoring the people around you, and continuously raising the bar for what "good" looks like in our data org.

Requirements

  • 5+ years of data engineering experience, with a track record of owning systems end-to-end
  • Strong SQL, Python, and data modeling skills — opinionated about design strategies and best practices
  • Hands-on experience with dbt and Snowflake
  • Experience with clickstream / event data
  • Demonstrated ability to design and ship scalable data systems
  • Comfort using AI tools (Claude Code, Cursor, or similar) as part of your daily workflow
  • Excellent written communication — clear documentation, well-scoped specs, and the ability to explain technical tradeoffs to non-technical partners
  • Strong project ownership: defining requirements as you go, communicating tradeoffs, and delivering results within timelines
  • Ability to leverage abstraction to solve complex problems

Nice To Haves

  • Experience designing semantic layers, metric stores, or data contracts
  • Experience building A/B testing or experimentation frameworks
  • Experience building or contributing to internal AI tooling — skills, agents

Responsibilities

  • Design, build, and maintain a simple, effective, and scalable data warehouse on Snowflake — with clean models, well-named fields, and documentation that makes the warehouse easy to use by downstream users and systems
  • Implement and manage data transformation with dbt to ensure reliable, well-tested pipelines
  • Develop and evolve data models, semantic layers, and metric definitions that support a wide range of business needs while keeping data consistent and accurate across the organization
  • Own data quality, observability, and testing that protects downstream consumers from broken or misleading data
  • Build and evolve internal AI tooling (skills, agents, etc) that makes the Data Engineering team more effective
  • Partner with analysts, product engineers, and business stakeholders to understand their needs, scope the right solution, and deliver outcomes
  • Mentor analysts and peers, fostering a culture of learning, rigor, and continuous improvement
  • Proactively identify operational issues and propose evolutionary solutions

Benefits

  • 90% of employee health and welfare benefits premiums & 65% of dependent benefits premiums
  • A 401(k) program with employer match
  • 15 paid vacation days (increases to 20 days on your 3rd anniversary), 12 observed national paid holidays, 9 sick days, and 16 paid volunteer hours per year
  • Our flexible work culture means 2 or more days in the office (hybrid) or 100% fully remote options available for most positions
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service