layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Senior Analytics Engineer at Alloy, New York City, NY

As a Senior Analytics Engineer, you will be a technical anchor for how Alloy models, governs, and exposes data. You'll work closely with Data Science, Product, Engineering, and client-facing teams to ensure our data assets are trustworthy, well-documented, and built for scale.
Design and build robust dbt models that serve as the authoritative foundation for analytics, machine learning features, and customer-facing data products.
Own and evolve our semantic layer defining metrics, dimensions, and business logic in a way that supports both internal consumers and emerging agentic tooling.
Partner with Engineering and Data Science to ensure our Snowflake data warehouse is well-structured, performant, and aligned with product needs.
Establish and champion best practices for data modeling, testing, documentation, and code review across the team.
Collaborate with client-facing and product teams to scope and deliver native warehouse data delivery to customers.
Identify and address data quality issues proactively, building the observability and governance frameworks that keep data trustworthy at scale.
Influence how Analytics Engineering is practiced at Alloy—this is a greenfield opportunity to set the standard.
Who we’re looking for We're looking for a Senior Analytics Engineer who combines deep technical craft with the instincts of a cross-functional partner. You don't just model data—you think about how it will be used, by whom, and what it needs to look like to be genuinely useful. An ideal candidate has:
5+ years of experience in analytics engineering, data engineering, or a closely related role, with a strong command of dbt and SQL.
Hands-on experience with Snowflake or a comparable cloud data warehouse, including performance tuning and warehouse design.
Experience building or maintaining a semantic layer or metrics layer (e.g., dbt Semantic Layer, MetricFlow, or similar).
A strong sense of data modeling fundamentals. You have opinions about when to denormalize, how to handle slowly changing dimensions, and what makes a model trustworthy.
Familiarity with data ingestion and CDC tooling; experience with Artie or similar streaming/replication tools is a plus.
The ability to partner effectively with Data Science, Engineering, and Product. You translate between technical and non-technical stakeholders without losing precision.
Experience establishing standards: testing frameworks, documentation practices, naming conventions, and review processes that teams actually follow.
Comfort working in an environment where the function is still being shaped—you see that as opportunity, not ambiguity.
Someone who embodies our shared Alloy values: be bold, get scrappy, collaborate, and celebrate our differences.
Must be local to New York City; hybrid work with Tuesday-Thursday in-office at our Union Square HQ.
Nice to Have's
Experience with native warehouse data delivery or data sharing patterns (e.g., Snowflake Data Sharing, Marketplace).
Background in fintech, financial services, or a similarly data-intensive regulated industry.
Exposure to agentic or LLM-based workflows and the data infrastructure that supports them.
Experience with BI tooling (e.g., Looker, Tableau) and how semantic layer investments connect to the presentation layer.
We're a lean team, so your impact will be felt immediately, and opportunities will grow as the company scales up. If this all sounds like a good fit for you, why not join us?

Senior Analytics Engineer

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