Data Platform Engineering Manager - Kraken

About the Role

Kraken's Data Platform team builds the 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, the platform processes billions of events daily across trading, compliance, and product systems.

As Data Platform Engineering Manager, you will lead the team responsible for Kraken's streaming and data platform layer—designing systems that move, transform, and serve data in real time. You will own the architecture around stream processing (RisingWave, Flink), drive the adoption of AI-powered automation across the data stack, and build foundational platform primitives for engineering teams across the organization.

Responsibilities

• Lead, mentor, and grow a distributed team of senior data platform engineers building real-time streaming infrastructure.
• Own the architecture and roadmap for high-volume data systems utilizing Spark, Kafka, Iceberg, RisingWave, and Apache Flink.
• Design and operate scalable data architecture serving trading, risk, compliance, analytics, and product teams.
• Drive adoption of AI automation and intelligent workflows, including automated data quality checks, pipeline orchestration, anomaly detection, and self-healing infrastructure.
• Partner closely 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 while balancing reliability, velocity, and cost efficiency at scale.
• Cultivate a culture of ownership, continuous learning, and technical excellence within a remote engineering organization.

Requirements

• 8+ years of experience in data engineering, platform engineering, or distributed systems, with at least 3 years managing engineering teams.
• Proven track record building data lakes in AWS (e.g., Spark, Athena, Iceberg, Parquet, Presto), including data modeling, data quality standards, and self-service tooling.
• Deep expertise in building and operating real-time data pipelines at scale using Kafka, Spark Streaming, Debezium, and CDC pipelines.
• Experience designing or integrating AI/ML-powered automation into data workflows (e.g., pipeline orchestration, automated remediation, LLM-integrated tooling).
• Strong programming proficiency in Python, Scala, or Java in production data platform contexts.
• Solid understanding of cloud-native data infrastructure on AWS (Glue, Athena, S3, EMR, Lambda, or equivalents).
• Experience managing, recruiting, and mentoring high-performing remote engineering teams.
• Demonstrated ability to translate long-term technical vision into executable quarterly roadmaps and balance competing stakeholder priorities.

Nice to Haves

• Production or evaluation experience with RisingWave or ClickHouse.
• Familiarity with LLM-based agents or workflow orchestration frameworks (e.g., LangChain, LangGraph).
• Background in cryptocurrency, digital asset trading systems, or high-throughput financial data.
• Experience building self-service data platform tooling for internal engineering teams.
• Contributions to open-source streaming or data infrastructure projects.