Team

Kraken's Data Platform team builds the real-time infrastructure that powers decision-making across one of the world's largest digital asset exchanges. We operate at the intersection of streaming data, large-scale platform engineering, and AI-driven automation — processing billions of events daily across trading, compliance, and product systems.

This role leads the team responsible for Kraken's streaming and data platform layer — designing systems that move, transform, and serve data in real time. You'll own the architecture around stream processing (RisingWave, Flink), drive adoption of AI-powered automation and workflows across the data stack, and build the platform primitives that the rest of engineering depends on.

Opportunity

Lead and grow a team of senior data platform engineers building Kraken's real-time streaming infrastructure

Own the architecture and roadmap for high-volume low-frequency data systems, with focus on data stack like Spark, Kafka, Iceberg, RisingWave, Apache Flink

Design and operate scalable data architecture that serves trading, risk, compliance, analytics and many product teams.

Drive adoption of AI automation and intelligent workflows — automating data quality checks, pipeline orchestration, anomaly detection, and self-healing infrastructure

Partner with ML/AI, analytics, and product engineering teams to deliver platform capabilities that accelerate their work

Evolve Kraken's data‑lake and warehouse architecture to support both batch and streaming workloads seamlessly

Set technical direction for the team — balancing reliability, velocity, and cost efficiency at scale

Hire, mentor,



and retain top‑tier platform engineers; build a culture of ownership and technical excellence

Skills You Should HODL

8+ years in data engineering, platform engineering, or distributed systems — with at least 3 years managing engineering teams

Experience and knowledge of building data‑lakes in AWS (i.e. Spark, Athena, Iceberg, Parquet, Presto), including data modeling, data quality best practices, and self-service tooling.

Strong expertise in building and operating real-time data at scale including Kafka, Spark Streaming, Debezium, and CDC pipelines.

Proven ability to manage competing priorities across multiple stakeholder groups — aligning platform investments with the needs of product, finance, compliance, analytics, and other teams

Strong communicator — able to explain risks, trade‑offs, and roadmap decisions to both senior technical audiences and non‑specialist stakeholders.

Experience designing or adopting AI/ML‑powered automation in data workflows — pipeline orchestration, intelligent monitoring, automated remediation, or LLM‑integrated tooling

Proficiency in Python, Scala, or Java in a production data platform context

Solid understanding of cloud‑native data infrastructure (AWS preferred — Glue, Athena, S3, EMR, Lambda,



or equivalents)

Track record of managing, recruiting, and developing high‑performing remote engineering teams

Ability to translate long‑term platform vision into executable quarterly roadmaps

Servant‑leadership style — you coach, unblock, and grow your engineers

AI‑ready to 10X the team efficiency and overall output.

Nice to Haves

Experience with RisingWave and/or Clickhouse specifically — either in production or in serious evaluation

Familiarity with LLM-based agents or AI workflow frameworks (e.g. LangChain, LangGraph, custom orchestration)

Background in cryptocurrency, trading systems, or high‑throughput financial data

Experience building self‑service data platform tooling for internal engineering consumers

Contributions to open‑source streaming or data infrastructure projects

Equal Opportunity

As an equal opportunity employer, we don’t tolerate discrimination or harassment of any kind. Whether that’s 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.

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.

📌 Data Platform Engineering Manager (Madrid)
🏢 Kraken
📍 Madrid