Senior Data Engineer | Snowflake | Airflow | dbt | Python | This role is for builders
Salary: $205,000 – $250,000 + competitive equity
Location: New York City - Full time onsite
Eligibility: US Residents Only
Requirement: Startup or high-bar tech environment experience (non-negotiable)
🚨 Please only apply if you have commercial experience with ALL of the following 🚨
- Snowflake - hands-on, at scale
- Data pipeline and orchestration tooling - Airflow, dbt, and/or SQLMesh
- Building and maintaining multi-terabyte data infrastructure
- Python for data engineering
- Startup or high-bar tech environment experience
- True IC ownership - you build it, you own it
🚀 Join a fast-moving, investor-backed AI company redefining how enterprise brands understand and activate consumer demand. You'll own the data infrastructure that powers an AI platform trusted by household-name clients across sport, finance, and consumer - built by an exceptionally high-talent-bar team with serious backing and serious ambition.
This isn't a slides-and-stakeholders role. It's hands-on, high-ownership data engineering at a company scaling fast with the runway to match.
ℹ️ Very Important Notes
- This role is for builders - if you're more comfortable presenting than building, this isn't for you
- 5 days onsite NYC
- You'll own a large-scale, proprietary data asset - scale matters, fragility doesn't
- Startup experience is a hard requirement, not a preference
Must-Haves
- Strong hands-on Snowflake experience at multi-terabyte scale
- Proven delivery of fast, resilient data pipelines and orchestration systems
- Proficiency with Airflow, dbt, and/or SQLMesh
- Python backend skills applied to data engineering workflows
- True IC mentality - design, build, ship, own
- Startup or VC-backed environment experience (or equivalent high-bar company)
- AWS infrastructure exposure
Bonus Experience
- Experience enabling AI or agentic access layers - AI retrieval and query interfaces, structured data orchestration
- Exposure to key business systems of record in sales and marketing
- Background in ML feature pipelines or data science workflows
- Degree from a top CS programme
Hands-On Experience With
- Snowflake and modern data warehouse architecture
- Pipeline orchestration - Airflow, dbt, SQLMesh
- Large-scale data integration and transformation
- AWS infrastructure
- Analytics engineering and data modelling
What You'll Be Doing
Pipeline & Platform Ownership
- Own analytics engineering and data modelling across a Snowflake-powered warehouse
- Build and scale integrations with key business systems as the data footprint grows
- Develop fast, resilient pipelines that underpin the core AI platform
AI Infrastructure
- Enable AI retrieval and query interfaces that make intelligent, real-time decisioning possible
- Build the data foundation that powers the platform's most advanced capabilities
Scale & Scope
- Work across a large-scale, proprietary data asset - this is serious infrastructure
- Expand your scope over time, with a clear path to leading the Data Engineering function as the organisation grows
What They're Looking For
- A true IC - hands on keys, not directing from a distance
- 4-8 years of experience building and scaling data infrastructure
- Scrappy, pragmatic, and obsessed with reliability and performance
- Someone who wants to grow with a company, not just execute a brief
If you've got the Snowflake chops, the startup scars, and the IC mentality to own data infrastructure at scale - get in touch for a fast response.