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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Infrastructure Engineer (Query Engine) - **Company:** zaimler, Inc. - **Location:** San Mateo, CA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Databases, Customer Data Management, Data Mapping, File Systems, Distributed Systems, Snowflake, Databricks - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/data-infrastructure-engineer-query-engine-zaimler-8999536 ## About the Role * Strong database fundamentals: you understand consistency models, transactions, and how storage layers actually work under the hood, not just how to query one * Experience running systems at real production scale, where naive approaches start to break down * A systems mindset: background in OS, file systems, distributed systems, or database internals, from industry or research * Ability to work from ambiguous, evolving problems rather than fully scoped tickets * A bias toward hands-on execution over pure architecture or process ownership, * Background at a data intensive company or research lab ## Description zaimler is building the next-generation semantic platform that links fragmented enterprise data and extracts meaning with knowledge-distilled models. We're creating the foundation for AI systems that don't just generate, but retrieve, link, and reason over enterprise knowledge. In just over a year, we've begun partnering with Fortune 500 design partners in insurance, travel, and technology, deploying our semantic platform into some of the world's most complex and high-volume data ecosystems. Our platform enables enterprises to make their data AI-ready from the start: automating ontology creation, data mapping, and retrieval-augmented reasoning at scale. Our team comes from LinkedIn, Visa, Meta, and Branch, and has spent decades solving data and infrastructure challenges at scale. Backed by top VCs, we're building the next foundational layer for enterprise AI. What You'll Do zaimler's query engine powers graph-native queries across a two-layer system: an internal storage and indexing layer, and a pass-through layer that queries live into customer data platforms like Snowflake and Databricks. You'll work across the engine's coordinator, compiler, and executor, extending language and function support, and helping build queries that reason across multiple data sources at once. What You'll Own * Extend the query engine's language and function support over time * Help build cross-source query capabilities: answering questions that span multiple data sources in a single query * Work on the storage and indexing layer that the query engine runs against * Build and maintain the layer that queries live into external systems like Snowflake and Databricks * Work directly in the engine's core components: coordinator, compiler, executor ## Related Videos - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)