Data Platform Engineering Manager

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.

Responsibilities

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 serve 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

Requirements

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 have

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