Senior Data Engineer - Agents Systems

Kraken; Greater London; On-site; GBP 60,000 - 80,000; Full time

Job summary

Kraken is seeking a Data Engineer in Greater London to own and evolve streaming data pipelines that power real-time model serving across our AI infrastructure. You will design and build feature stores, implementing low-latency solutions and ensuring high data quality.

The ideal candidate has 5+ years in data engineering with a focus on streaming systems in production and expertise in Python or Scala. Join our dynamic team at the forefront of open finance.

Qualifications

• 5+ years in data engineering with at least 2 years focused on streaming systems.
• Hands-on experience with RisingWave, Apache Flink, or Kafka Streams.
• Strong understanding of feature store design and low-latency serving.

Responsibilities

• Own and evolve streaming data pipelines for Kraken's AI infrastructure.
• Design and build feature stores for production ML models.
• Implement and maintain streaming systems using appropriate tools.

Skills

Data engineering

Streaming systems

Python

Scala

SQL

Tools

RisingWave

Apache Flink

Kafka Streams

Job description

Building the Future of Open Finance

Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system.

Before you apply, we encourage you to explore our culture page to understand what drives us and how we work.

Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.

The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration.

This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools.

You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.

The opportunity

• Own and evolve streaming data pipelines that power live inference and real-time model serving across Kraken's AI infrastructure
• Design and build feature stores that serve low-latency, high-reliability features to production ML models
• Implement and maintain streaming systems using RisingWave, Apache Flink, or Kafka Streams, selecting the right tool for the workload
• Partner with ML engineers and AI infra teams to define data contracts, feature schemas, and pipeline SLAs
• Drive pipelines toward real-time where batch exists today reducing latency from hours to seconds
• Ensure data quality, observability, and auditability across all streaming and feature engineering systems
• Contribute to inference pipeline tooling where data engineering and model serving intersect
• Evaluate emerging streaming and feature store technologies and shape the team's technical roadmap

What You Bring

• 5+ years in data engineering with at least 2 years focused on streaming systems in production
• Hands‑on experience with RisingWave, Apache Flink, Kafka Streams, or comparable stream processing frameworks
• Strong understanding of feature store design — online/offline consistency, point‑in‑time correctness, low‑latency serving
• Experience building data pipelines that feed production ML models or inference systems
• Proficiency in Python and/or Scala; SQL fluency required
• Familiarity with data quality frameworks, pipeline observability, and SLA ownership
• Comfortable operating in a fast‑moving, ambiguous environment embedded within an AI‑focused team

Nice to haves

• Direct experience with RisingWave in production
• Exposure to inference pipeline architecture or model serving infrastructure
• Experience with feature platforms
• Crypto or fintech domain experience

Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.

Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.

We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.