5+ years of experience in analytics, data, or reporting engineering
2+ years of hands-on dbt development
Experience building AI-assisted workflows for data modeling and testing
Advanced SQL proficiency with a focus on performance and readability
Hands-on experience with ETL/ELT and data warehousing principles
Familiarity with tools like Snowflake, dbt, Hex, Segment, Matia, Fivetran, and Airflow preferred
Responsibilities
Own the architecture of the dbt project, ensuring consistency and best practices
Collaborate with product, design, and engineering teams to support new features
Build and optimize dbt models for scalable datasets, iterating weekly
Design automated testing and documentation workflows using AI
Shape ingestion and transformation pipelines with data engineering
Drive data privacy, governance, and quality standards
Benefits
Competitive health and dental insurance from day one
Flexible PTO policy
In-office lunch twice a week and dinner stipends
Access to Wellhub for wellness resources and gym discounts
Annual stipend for professional development
$5,000 bonus for high performers after 5 years
401k eligibility from day one
Dependent Care FSA
Paid parental leave
Fertility and adoption benefits
Full Job Description
About the Role
As a Senior Analytics Engineer, you'll own how Genius AI models, defines, and trusts its data. You sit at the intersection of data and the business, curating data so that it can be used to drive insights, strategy, and decision making. Our agentic products are scaling and our architecture is moving toward a more software-oriented model, which means the dbt project you design now will set the standard for how we understand customer behavior and how our AI-powered products make decisions. You won't inherit a finished playbook. You'll write one, and you'll ship changes in days, not quarters, with the judgment to know when to slow down. We expect you to challenge how we work, not just execute against it.
You will report to the Analytics Engineering Manager. You must be commutable to our NYC headquarters and will operate in an in-person environment. We default to being in-office 3-4 days per week with required attendance on Tuesdays and Thursdays.
What You'll Do
Own the architecture of our dbt project, including design patterns, modeling standards, and the best practices that keep a fast-growing codebase consistent through staging, intermediate, and mart layers
Partner with PDE (product, design, engineering) teams to support new features and architectural changes by reviewing design docs, creating or updating dbt models as data sources evolve, and validating that metrics, reports, and downstream consumers stay accurate
Build, refactor, and optimize dbt models that turn raw product and customer data into accurate, scalable datasets, iterating on a weekly cadence and correcting fast when the data says we're wrong
Use AI to build, not just work: design automated testing, documentation, and data-access workflows that scale beyond your own capacity and free your judgment for the problems that need it
Collaborate with data engineering to shape ingestion and transformation pipelines across Segment, Fivetran, and Airflow as we move toward a software-oriented architecture
Drive data privacy, governance, and quality standards that protect the integrity of the data our customers trust us with
What We're Looking For
5+ years of experience as an analytics engineer, data engineer, or reporting engineer, with 2+ years of hands-on dbt development
You've built AI-assisted workflows for modeling, testing, or documentation rather than only using AI-assisted editors
Default to action: you set a direction, ship something, and iterate on what you learn instead of waiting weeks for perfect alignment
Advanced SQL proficiency, with a track record of writing models that stay fast and readable as data volume grows
Hands-on experience with data modeling, ETL/ELT development principles, and data warehousing concepts
