Software Engineer, Data Products & Platform

The posting, as Clay Labs wrote it

ABOUT CLAY

AI is unleashing the biggest wave of company creation in history. Clay's mission is to be the engine those companies use to grow to their full potential.

Clay predicts the next best action for your business and then helps you take it. We started by aggregating the best data for B2B companies. Then, we built the infrastructure to run any personalized campaign on top of it, including emails, ads, landing pages, and workflows that make reps more productive. Now, we're building agents that can help grow your company for you. We're already helping thousands of customers — including Anthropic, OpenAI, Google, and Visa — go to market with unique data, signals, and AI research.

In 2026, we raised a $115M Series D https://www.linkedin.com/safety/go/?url=https%3A%2F%2Fwww.nytimes.com%2F2026%2F09%2F09%2Fbusiness%2Fdealbook%2Fclay-ai-fundraising.html%3Fsmid%3Durl-share%26unlocked_article_code%3D1._1A.E5rN.MeYsbgEsUKbB&urlhash=XS4q&mt=4bpSf4a8omAKuAHqAqZx6C11QpbLK_QwIhSV7gSf4Wf9aywPF_KBSiX9IkWE1AhXBEjPH8mK6fAEN7CMFlpvo0lPAtKRjs-dhgzYqHiVKUMCRtw0jScFgxWCRRfYs4HCX0YL9L6PCQz-edBLinvRdU_TaVUL2dA3&isSdui=true&lipi=urn%3Ali%3Apage%3Ad_flagship3_feed%3BoQmIsufoRJm7X2HC5Rqd%2Fw%3D%3D at $7.1B Valuation led by Wellington — and are on track to cross $200M in revenue this quarter. We also launched a $1M Scholarship fund for GTME Education.

Some things to know about us

• Our community http://community.clay.com includes 17,000+ customers, 200+ integration partners, 125+ agencies, 50+ Clay clubs https://luma.com/claylive, and 30k members on Slack.
• Our culture https://nextplayso.substack.com/p/spotlight-clay is unique inside and outside of work. Our team members are also DJs, activists, writers, clowns, marathoners, skydivers, psychedelic therapists, social workers, and more.
• All employees can work with world-class coaches who specialize in creativity, management, and more.
• Our operating principles — including negative maintenance and non-attached action — guide our work. Read more about them here https://cdn.prod.website-files.com/61477f2c24a826836f969afe/685d83a71452245cc1129791_4d770abfd83e276ec15315a2e06945bd_Clay2025_OperatingPrinciples.pdf.
• Read about us in the NYT https://www.nytimes.com/2025/08/05/business/dealbook/clay-ai-marketing-fundraise.html, Forbes http://google.com/search?q=forbes+clay&rlz=1C5OZZY_enUS1155US1155&oq=forbes+clay&gs_lcrp=EgZjaHJvbWUyBggAEEUYOTIHCAEQABiABDIHCAIQABiABDIHCAMQABiABDIHCAQQABiABDIHCAUQABiABDIHCAYQABiABDIHCAcQABiABDIHCAgQABiABDIHCAkQABiABNIBBzkzM2owajSoAgOwAgHxBVAe8UAxJx_p&sourceid=chrome&ie=UTF-8, First Round Review https://review.firstround.com/podcast/inside-clays-unconventional-path-to-1-25b/, and more https://www.clay.com/press.

Hear from our employees directly on our Glassdoor https://www.glassdoor.com/Overview/Working-at-Clay-EI_IE9850794.11,15.htm page!

THE ROLE

Data Platform at Clay doesn't sit behind the product. The team builds data products customers use directly, and the
[…]
collaborate with others to ship high quality, thoughtful features. You talk to customers, consider multiple approaches, and work with teammates to find the right solution. You care about craft, write clear and maintainable code, and create frameworks and reusable patterns that eliminate classes of problems, not just point fixes.

• Having a diversity of perspectives is important to you. You believe that having people with different backgrounds and perspectives creates a better team and a more holistic product.
• You’re familiar with our current tech stack or can learn unfamiliar technologies quickly. You don't need experience with every technology listed:
• Product stack: React, TypeScript, Python, Node.js, Aurora PostgreSQL, Redis, ECS Fargate, Lambda, OpenSearch
• Data platform: Python, SQL, Iceberg on S3 with Glue and Athena, SQLMesh, ClickHouse, Airflow, Terraform
• Observability: Datadog, CloudWatch
• You've built and operated production systems where data quality and reliability both matter.
• You're comfortable in SQL and Python, and can reason about data models, distributed jobs, lineage, and failure recovery.
• When a customer gets a wrong answer, you treat it as your bug, wherever it came from.
• When datasets disagree or the right quality bar isn't obvious, you measure the problem and improve from evidence. You'd rather bring that evidence to Product or Data Science than argue positions.

NICE TO HAVES

• Experience with entity resolution, graph data, or temporal data.
• Experience putting an LLM in the critical path of a shipped product, including how you proved it was correct.
• Experience with search infrastructure or data-intensive product systems.
• Experience evaluating and operating on large third-party datasets.

OUT OF SCOPE

This isn't an analytics, BI, or warehouse-enablement role, and it isn't pure infrastructure. The team owns whether each data product is correct, useful, and fast enough for customers.