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Join Kraken as a Data Platform Engineering Manager to lead a team in building real-time streaming infrastructure for one of the world's largest digital asset exchanges. Drive AI automation and technical excellence in a fully remote environment.
Kraken is a mission-focused company rooted in crypto values, aiming to accelerate the global adoption of crypto for financial freedom and inclusion. As a fully remote company with Krakenites in 70+ countries, it develops premium crypto products for experienced traders, institutions, and newcomers, with a focus on security, education, and world-class client support through products like Kraken Pro, Desktop, Wallet, and Kraken Futures. The Data Platform team builds real-time infrastructure powering decision-making across one of the world's largest digital asset exchanges, operating at the intersection of streaming data, large-scale platform engineering, and AI-driven automation, processing billions of events daily.
Responsibilities
- Own the architecture and roadmap for high-volume low-frequency data systems.
- Focus on data stacks like Spark, Kafka, Iceberg, RisingWave, and Apache Flink.
- Design and operate scalable data architecture for trading, risk, compliance, analytics, and product teams.
- Drive adoption of AI automation and intelligent workflows (e.g., data quality, pipeline orchestration, anomaly detection).
- Partner with ML/AI, analytics, and product engineering teams.
- Evolve data-lake and warehouse architecture for batch and streaming workloads.
- Set technical direction, and hire, mentor, and retain top-tier platform engineers while fostering a culture of ownership and technical excellence.
Qualifications
- 8+ years in data engineering, platform engineering, or distributed systems.
- At least 3 years managing engineering teams.
- Experience and knowledge of building data-lakes in AWS (Spark, Athena, Iceberg, Parquet, Presto).
- 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.
- 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, AI-ready to 10X team efficiency and overall output.
- Nice to haves: experience with RisingWave and/or Clickhouse specifically, 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.