Data Engineer – AI Product Analytics

About PIP Labs & Story

PIP Labs is an R&D company contributing to the development of Story, a purpose-built Layer 1 blockchain that transforms intellectual property into a programmable asset class.

Story is designed specifically for intellectual property. With Story, creators and developers can register IP on-chain and define usage rights in seconds, dramatically lowering the barriers created by today’s complex and antiquated IP legal systems.

By making IP programmable, Story creates a transparent, decentralized global repository where AI agents, developers, and businesses can discover, license, and monetize intellectual property through simple API-driven interactions.

Story launched mainnet in February 2025, and the native $IP token is now listed on major global exchanges. We are now entering the next phase of development focused on AI-native infrastructure and agent-driven applications built on top of programmable IP.

PIP Labs is building the core infrastructure that powers this ecosystem, defining how intellectual property is registered, structured, and transacted in an AI-driven world.

As a Data Engineer, you will build the data infrastructure that powers analytics and decision-making across the Story ecosystem.

You will design and operate data pipelines that transform onchain activity and product data into reliable, accessible datasets. Your work will enable teams across engineering, product, and ecosystem to understand usage patterns, measure growth, and make informed decisions.

This role is ideal for engineers who enjoy building robust data systems and turning complex blockchain and product data into clear, actionable insights.

• Design and maintain reliable data pipelines that ingest and process onchain and product data

• Build datasets and data models that support analytics, reporting, and experimentation

• Develop dashboards and metrics that provide clear visibility into ecosystem and product performance

• Partner with product and engineering teams to define measurement frameworks and success metrics

• Improve data quality, consistency, and observability across the analytics stack

• Support ad-hoc analysis and data needs across the organization

• Strong experience with SQL and Python

• Experience building and maintaining data pipelines

• Experience working with modern data warehouses and analytics tools

• Strong understanding of data modeling and analytics workflows

• Product-oriented mindset with a focus on measurable outcomes

• Careful, detail-oriented approach to data quality and reliability

• Comfortable working in a fast-moving environment

• Experience working with blockchain or onchain data

• Experience building analytics for developer platforms or marketplaces

• Experience with real-time or streaming data pipelines

• Experience supporting experimentation or growth analytics