Senior Data Engineer – AI Infrastructure

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Kraken Digital Asset Exchange

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

Kraken Digital Asset Exchange is a cryptocurrency platform that facilitates the buying and selling of over 200 cryptocurrencies, including Bitcoin, Ethereum, and many others. Founded in 2011, Kraken provides a comprehensive suite of features for both beginner and advanced traders, such as advanced trading interfaces and margin trading. The platform emphasizes industry-leading security, deep liquidity, and 24/7 customer support, making it a trusted choice for users worldwide. Kraken caters to individual investors as well as institutional clients, offering services like OTC trading and custody. The company is committed to transparency with its proof of reserves and mission-driven values. Kraken operates globally, supporting clients in over 190 countries, with a quarterly trading volume exceeding $207 billion. However, users are advised of the high risk of crypto investments and the lack of regulation in some jurisdictions.

📋 Description

• 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

🎯 Requirements

• 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.

🏖️ Benefits

• 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.