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Summary: 

As a Senior Data Engineer on the Analytics team, you'll help shape the architecture and long-term direction of our data platform while building and maintaining reliable, scalable data systems that power decision-making across the company. You'll partner closely with data analysts, product managers, designers, and engineering teams to translate business and product needs into durable technical solutions. In this role, you'll also mentor teammates, champion data quality and best practices, and help elevate the overall maturity and impact of our data organization.

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

Minimum Qualifications:

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
Preferred Qualifications
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