Analytics Engineer

Clay is a creative tool for growth. Our mission is to help businesses grow  — without huge investments in tooling or manual labor. We’re already helping over 100,000 people grow their business with Clay. From local pizza shops to enterprises like Anthropic and Notion, our tool lets you instantly translate any idea that you have for growing your company into reality.
We believe that modern GTM teams win by finding GTM alpha—a unique competitive edge powered by data, experimentation, and automation. Clay is the platform they use to uncover hidden signals, build custom plays, and launch faster than their competitors. We’re looking for sharp, low-ego people to help teams find their GTM alpha.

Why is Clay the best place to work in New York?

• Customers love the product (100K+ users and growing)

• We’re growing a lot (6x YoY last year, and 10x YoY the two years before that)

• Incredible culture (our customers keep applying to work here)

• Well-resourced (raised a Series B expansion in January 2025 from investors like Sequoia and Meritech)

Read more about why people love working at Clay here and explore our wall of love to learn more about the product.

We’re looking for an Analytics Engineer to bridge the gap between raw data infrastructure and high-impact business insights and data products. You’ll take ownership of our data models, pipelines, and platform architecture to ensure our analytics and data science foundation is scalable, durable, and consumable. Your work will enable better decision-making across teams - from Product and Engineering to Marketing, Finance, and Ops.

Clay’s modern data stack includes Fivetran, Segment, Snowflake, dbt, Dagster, Hex, Sigma, Eppo, Census, Cube.dev, and you'll play a key role in shaping how we use and evolve it to power strategic insight and operational excellence.

• Own data pipelines: Design, build, and maintain reliable ETL/ELT pipelines, ensuring timely and accurate delivery of high-quality data across the organization

• Build a scalable foundation: Find ways to leverage and improve our current data models by architecting resilient, maintainable dbt models that serve as the trusted source of truth for analytics, experimentation, and data products

• Collaborate cross-functionally: Work closely with data scientists, engineers, and business teams to understand use cases and proactively develop data assets that support their goals effectively and scalably

• Drive architectural improvements: Identify opportunities to consolidate and improve our data platform, proposing improvements that ensure long-term scalability and flexibility

• Improve data quality, discoverability, and metric clarity: Design and implement robust systems for schema design, data validation, documentation, and governance, while defining and standardizing core business metrics and semantic definitions to ensure consistency across teams and tools

• Support self-serve insights: Enable teams with intuitive, trustworthy data products and tooling that allow less-technical users to explore data and develop solutions independently

• Plan for the future: Help define the evolution of Clay’s data stack and architecture, including how we consolidate, transform, and surface data and intelligence for emerging use cases

• 6+ years of hands-on experience in analytics engineering, data engineering, or data management

• Strong ownership mentality and proven ability to design for scalability, durability, and reusability

• Expert in SQL, Python, AWS infrastructure, and modern data tools (emphasis on dbt, Dagster/Airflow)

• A passion for pragmatic solutioning while staying current on modern data and AI tooling, pushing the boundaries of GenerativeAI’s role in Data Products and workflows

• Excitement for iterative, agile development processes and collaboration with diverse teams