SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Zaimler is building the next generation of enterprise data infrastructure to democratize data discovery and preparation for the AI era. The company bridges the gap between business knowledge and data, helping organizations make their data AI-ready faster and more reliably. Founded by seasoned data infrastructure and ML experts from LinkedIn, Visa, Truera, Hive, and Branch, Zaimler is backed by top-tier VC funds and operates from San Mateo with a collaborative, onsite-first culture.
As a Data Infrastructure Engineer focused on Query Engine development, you will design and build scalable, fault-tolerant query engines optimized for performance and resource efficiency. Your responsibilities include architecting distributed systems solutions that handle concurrency, scalability, and reliability at petabyte scale. You'll apply advanced optimization techniques such as vectorized processing, cost-based optimization, and intelligent caching to enhance query execution performance.
Key technical work includes developing integrations with modern data lake formats (Apache Iceberg, Delta Lake, Hudi) and semantic layers, contributing to or extending open-source platforms like Apache Spark, Presto, and Trino to meet unique product requirements. You'll research and implement the latest advancements in query processing and distributed systems, staying at the cutting edge of the field.
You'll collaborate closely with product, data science, and engineering teams to align technical solutions with business needs, working in an environment that values transparency, purpose-driven innovation, and collective leadership. The role offers the opportunity to build robust systems from scratch in an early-stage startup setting, with mentorship and engineering culture-building as key responsibilities.
Required qualifications include deep proficiency in Java, Scala, Rust, or C++; strong understanding of query engine internals, distributed systems architecture, and parallel query processing; hands-on experience with Apache Spark, Presto, or Trino; and proven ability to optimize systems handling petabyte-scale datasets. SQL semantics, execution plans, and query optimization expertise are essential.
Nice-to-have skills include experience building AI/ML infrastructure and ML production systems at scale, hands-on Linux and Docker containerization experience, and prior work at early-stage startups. The company sponsors H-1B visas and supports immigration processes.
