Data Infrastructure Engineer at zaimler

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

0.0

Posted On

04 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Distributed Data Systems, Spark, Kafka, Flink, Ray, Python, Scala, Java, Kubernetes, Cloud Environments, AWS, GCP, Azure, Streaming, Batch Systems, Collaboration

Industry

Description

About zaimler zaimler is building the 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 semantic AI infrastructure into some of the world’s most complex data ecosystems. Our platform enables enterprises to make 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. The Role We’re looking for a Data Infrastructure Engineer to help build the foundational distributed data layer that powers our semantic platform. You’ll design, build, and scale systems for high-throughput data ingestion, transformation, and real-time processing, shaping the backbone that makes our knowledge layer possible. As one of the early members of our Bangalore office, you’ll play a key role in setting the technical direction, culture, and standards for our growing team. \n What You’ll Do Build and operate large-scale data pipelines on Spark, Kafka, and Ray. Design fault-tolerant streaming and batch systems that move terabytes reliably. Optimize data workflows for performance, cost, and latency. Collaborate with ML and product engineers to ensure data is discoverable, structured, and queryable. Automate deployments with Kubernetes, Terraform, and CI/CD pipelines. Monitor, debug, and improve distributed jobs in production. What We’re Looking For Deep experience with distributed data systems (Spark, Kafka, Flink, Ray). Strong programming skills (Python, Scala, or Java). Comfort with Kubernetes and cloud environments (AWS/GCP/Azure). Solid understanding of streaming vs. batch tradeoffs, state management, and scaling patterns. Ability to collaborate across data, infra, and ML teams. Why Join A rare opportunity to be an early engineer in our Bangalore office, shaping both the company’s direction and the core product from the ground up. Competitive salary, full benefits, and meaningful equity. Work alongside engineers and researchers from LinkedIn, Visa, Meta, and Branch. An onsite, high-collaboration culture designed for deep technical work and fast iteration. Comprehensive benefits package (health insurance, meals, equipment, and other local perks). \n

Responsibilities

You will design, build, and scale systems for high-throughput data ingestion, transformation, and real-time processing. Your work will shape the backbone that makes the knowledge layer of the semantic platform possible.