Data Platform Engineering Manager

职位要求 / 描述

BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. Before you apply, we encourage you to explore our culture page https://www.kraken.com/culture to understand what drives us and how we work. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. 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.   THE 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 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   WHAT YOU BRING - 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 g

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