Honeycomb is looking for a Data Engineer to expand its data modeling layer, build trustworthy foundations for analytics, and enable teams across the company with scalable, reliable data to support business growth.
Requirements
- 3–5+ years of experience in data engineering or analytics engineering
- Mastery of SQL and dbt, with an eye for structure, testing, and maintainability
- Working experience with Python, especially for data ingestion, orchestration, and basic scripting
- Comfort working with cloud data warehouses like Snowflake (or Redshift, BigQuery)
- Experience implementing structured data models, architectures and marts
- Strong intuition around data contracts, late-arriving data, slowly changing dimensions, and business logic edge cases
- Hands-on usage of AI tooling in your data engineering workflow (e.g., Copilot for dbt model stubs, AI-assisted test generation, documentation, SQL generation/refactoring, or code reviews)
Responsibilities
- Own and expand our dbt modeling layer, ensuring it is structured, documented, and reliable
- Ingest and normalize data from diverse systems (e.g. Stripe, Salesforce, Hubspot, Netsuite) via Fivetran and custom pipelines
- Build analysis-ready marts that power dashboards, experimentation, and planning
- Partner with our Staff Data Engineer on ingestion architecture and orchestration, while taking the lead on modeling and semantic logic
- Ensure data quality via testing, validation frameworks, and proactively identifying upstream issues
- Create leverage through documentation, code reusability, and adoption of AI-assisted tooling to boost development velocity, reduce manual overhead, and enhance documentation/testing
- Explore generative AI, LLMs, and agent workflows where they make sense (e.g., schema mapping, anomaly detection, code validation)
Other
- Collaborate with stakeholders across the business to understand how data is used and what it needs to represent
- Comfort working through ambiguous situations - our data team is small and young so some role shaping and willingness to work across the data stack (e.g. occasional dashboard building, analysis) is critical to early success in this role
- Strong intuition around data quality and governance including experience developing tests and building out documentation
- Experience working across functions (e.g., Finance, Product, CS) to map business needs into durable models
- A mindset of ownership, iteration, and clarity — you care about the business logic behind the data, and building systems others can trust and build on
- Please note we cannot currently sponsor or support visa transfers at this time.
- Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work.
