About the role

DATA ENGINEERING LEAD About Patlytics: Patlytics is the fastest-growing AI-native patent intelligence platform, transforming how IP is protected and monetized at scale. Our advanced LLMs and generative AI engine—custom-built for intellectual property—power every phase of the patent workflow from invention disclosure through litigation, delivering citation-backed insights with unprecedented accuracy and speed. Fresh off our $40M Series B — led by SignalFire https://www.linkedin.com/company/signalfire/, with participation from N47 https://www.linkedin.com/company/n47capital/, Myriad Venture Partners https://www.linkedin.com/company/myriad-vp/, Liquid 2 Ventures https://www.linkedin.com/company/liquid-2-ventures/, BAM Corner Point https://www.linkedin.com/company/bam-corner-point/, Alumni Ventures https://www.linkedin.com/company/alumniventures/, Antiportfolio Ventures https://www.linkedin.com/company/antiportfolio-ventures/ and Relativity https://www.linkedin.com/company/relativityhq/- allows us to triple down on the product, accelerate growth globally, hire future mission-aligned colleagues, and to continue redefining what is possible for our customers. — we're scaling fast across product, engineering, and go-to-market. If you want to build at the inflection point, this is it. With teams across the globe we're building a global company fueled by exceptional talent and bold ideas. Our rapid expansion is driven by people who bring entrepreneurial energy, intellectual curiosity, and a shared commitment to setting the global standard for AI-powered IP intelligence. We're creating a culture where diverse perspectives shape breakthrough innovation and every voice contributes to transforming how the world protects ideas. We hire for trajectory, not just credentials. If you're 70% of this list and hungry to close the gap, apply. The Role: As the Data Engineering Lead, you'll own our data warehouse and everything around it — the pipelines that feed it, the models built on top of it, the metering our billing depends on, and the reporting the company makes decisions from. This role is heavy on backend and infrastructure, specialized in data. It's hands-on and it's a lead role, and both halves are real. You'll be writing production code and setting the architecture, and you'll grow into leading the team we build behind it. If you want to own a layer of the company outright rather than pick up tickets on someone else's roadmap, this is that job. As the Data Engineering Lead, you’ll: - Own the design, build, and operation of our data warehouse and transformation layer, from schema design through performance and cost - Build the ingestion pipelines that feed it, and own their reliability - Design and own the data models behind usage metering and billing - Stand up and maintain BI and reporting so leadership, product and GTM can answer their own questions instead of filing a ticket and waiting - Set the standards for data quality, testing, documentation, and monitoring, and hold the bar on them as the surface area grows - Work directly with CTO on what we instrument and why, and turn vague business questions into models that actually answer them About you: - Proven experience building and operating a production data warehouse and transformation layer: Snowflake, dbt, Redshift, or comparable stacks - Hands-on experience with BI and visualization tooling, including the data models that sit beneath it and the metric definitions the business relies on - Prior experience supporting a billing system, with a clear understanding of the downstream impact when billing data is inaccurate - Strong production experience in Python, alongside advanced SQL. This is a hands-on engineering role - A track record of carrying problems from ambiguity through to resolution, and the appetite for the scope this role carries - Interest in leading through technical direction and influence rather than headcount - A