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zaimler

AI readiness platform for enterprise data

Data Infrastructure Engineer - Query Engine

Systems Software EngineeringUpdated on Nov 10
Full-timeSan Mateo, CA, USA

About the Job

Requirements

  • Strong database fundamentals, including consistency models, transactions, and how storage layers work internally.
  • Experience with ordered key-value stores such as FoundationDB, TiKV, or RocksDB-backed systems, including designing index layouts, range scans, and transaction limits.
  • Experience running systems at production scale where naive approaches start to break down.
  • A systems background in operating systems, file systems, distributed systems, or database internals, from industry or research.
  • Experience with federated or distributed queries, including cross-source joins, filter and projection pushdown, semi-join and key-seeded lookups, cost-based join ordering, and late materialization.
  • Experience with graph query languages such as Cypher, openCypher, or GQL semantics, including pattern matching, variable-length traversal, and path semantics.
  • Experience with gRPC and protobuf contract design, including evolving wire contracts between services without breaking them.

Responsibilities

  • Extend the query engine’s language and function support over time.
  • Help build cross-source query capabilities that answer questions spanning multiple data sources in a single query.
  • Work on the storage and indexing layer used by the query engine.
  • Build and maintain the layer that queries live into external systems such as Snowflake and Databricks.
  • Work directly in the engine’s coordinator, compiler, and executor components.
  • Work on query optimization and aggregations that span multiple data sources.

Desired Qualifications

  • ANTLR grammar experience.
  • API development experience.
  • Prior experience at an early-stage startup developing systems and processes from scratch.
  • Knowledge of knowledge graphs and ontologies.
  • Experience with data connectors.
  • Experience with agentic systems.

About the Company

zaimler

AI readiness platform for enterprise data

Zaimler builds an enterprise data platform that makes data AI-ready by simplifying and organizing complex datasets for advanced applications. The platform ingests and structures enterprise data, automates taxonomy creation and knowledge-graph representations, and processes data at scale to prepare datasets for machine learning and business intelligence. Led by veterans from LinkedIn, Meta, and Visa, it targets large enterprises with a focus on automating taxonomies and knowledge graphs, backed by venture funding and early design partnerships in a B2B subscription model. Its goal is to become the standard platform that unlocks the value of enterprise data for AI-driven decision making.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
Not listed

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