Senior Data Engineer

THE ROLE

Kai is hiring a Sr. Data Engineer to join our data infrastructure team. This is a hands-on, high-ownership role at the core of what we do — we live on ingesting and processing data atvery highspeed, and this person owns the systems that make that possible.

You will design, build, andoptimizethe data pipelines and infrastructure that power Kai's securityplatform across some of the largest enterprises in the world. This is not an advisory role. You are expected to architect and implement,toidentifywhat needs to change, and start working on it.

We are building a world-class data function. The person who joins now will haverealinfluence over how that function evolves.

WHAT YOU'LL DO

• Design and build scalable data pipelines for batch and real-time processing across Kai'sagentic AIplatform

• Own andoptimizehigh-volume data infrastructure handling hundreds of millions of entries with low latency and high reliability

• Build andmaintaindata models and storage systemsoptimizedfor large-scale, high-throughput security data workloads

• Identifybottlenecks in the current architecture and drive optimization — reduce processing time, improve reliability, and make the customer experience better

• Lead the Terraformization of data pipelines to enable cloud-agnostic deployment across Azure, AWS, and GCP

• Integrate and manage cloud data services, ensuring secure service principles, permissions, and cross-service connectivity

• Collaborate closely with Backend Engineering teams on both the ingestion and consumption sides of the data pipeline

• Ensure data quality, consistency, and reliability across all pipelines

• Contribute to code reviews, technical documentation, and best practices

• Bring a point of view — propose solutions, not just problems, and start building beforeyou'reasked

WHAT YOU'LL BRING

Required:

• 7+ years of experience in data engineering or data platform engineering

• Must have hands-on experience handling up to 200M+ entries in materialized views in an asynchronous manner

• Strongproficiencyin Python and SQL — these are how our systems are written

• Strong data modeling skills — you can design schemas and storage systems that hold up at scale

• Experience with NoSQL databases at scale —CosmosDB, MongoDB, or equivalent

• Proven experience designing and building large-scale distributed data pipelines in both batch and streaming modes

• Hands-on experience withFlink,Kafka, Spark, or similar stream and batch processing frameworks

• Experience with data pipeline orchestration tools — Airflow, Temporal, or equivalent

• Infrastructure experience — Terraform, Kubernetes, and Docker are expected, not aspirational

• Cloud platformexpertise— deep hands-on experience in at least one major cloud platform (Azure, AWS, or GCP); Azure experience strongly preferred

• Strong communicationskills — you work cross-functionally and can explain complex systems clearly

Preferred:

• DataOpsexperience — ability to own data infrastructure decisions independently, reducing dependency on DevOps for pipeline deployment, permissions, and service integration

• Experience with data systems supporting AI/ML workloads — feature stores, ML pipelines, or dataset versioning

• Experience withDeltaLake, Apache Iceberg, or similar open table formats

• Startup or high-growth experience — you haveoperatedin a fast-paced environment where things change quickly, and ownership is expected