Senior Data Engineer

✨ One platform, a whole world of opportunity

The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere.

We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing:

Ranked #10 of 250 on TIME and Statista's 2026 list of America's Top WorkTech Companies

Named one of America's Greatest Startup Workplaces 2026 by Newsweek

A G2 Spring 2026 Leader across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance

The only B Corp-certified global employment platform ~ independently verified since 2023

Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one.

And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply.

👩‍💻 The Role

Location: While this position is posted in a specific location, all of Oyster’s positions are fully remote and you can work from home. Forever. To create the best experience for our new hire, this role requires you to be based within UTC−6 to UTC+3.

Oyster’s Data Engineering team is building the foundational AI platform layer that will enable teams across Oyster to develop, deploy, and operate secure, production-grade AI capabilities. As a Senior Data Engineer focused on AI Platform, you’ll work at the intersection of data engineering, platform engineering, and applied AI. You’ll build the data pipelines, services, integrations, and reusable platform capabilities that power AI use cases across Oyster.

You’ll leverage Oyster’s existing AWS and Snowflake data platform to make enterprise data accessible, reliable, secure, and useful for AI, supporting capabilities such as LLMs, RAG, embeddings, vector search, AI agents, tool calling, and AI workflows.

This is not a traditional data engineering role focused primarily on analytics pipelines or reporting. You’ll help define and build the data and platform foundations that let AI systems move from experimentation to reliable production, working closely with Engineering, Product, IT, and other teams across Oyster.

Key Responsibilities

Design and build data pipelines and platform capabilities that support AI applications, knowledge systems, and AI workflows.

Build and maintain data and knowledge pipelines for ingestion, transformation, chunking, embeddings, retrieval, vector search, metadata, and knowledge management.

Develop secure, reusable ways for AI systems to access enterprise data and systems using APIs, MCP, tool calling, and similar patterns.

Build reusable services, libraries, frameworks, and developer tooling that make it easier for engineering teams to build and productionize AI capabilities.

Apply strong data engineering practices around data modeling, data quality, lineage, access, reliability, and governance to AI-related data and systems.

Help establish patterns for AI deployment, observability, evaluation, and lifecycle management, including quality, latency, reliability, security, and cost.

Partner with engineers and stakeholders to take AI use cases from prototype to production, ensuring the underlying data and infrastructure are scalable and maintainable.

Ensure AI platform capabilities meet Oyster’s security, privacy, access control, and data governance requirements.

Evaluate emerging AI and data technologies and determine where they can create meaningful value for Oyster.