Data Platform Engineering Manager

🕒 April 24

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Logo of Kraken Digital Asset Exchange

Kraken Digital Asset Exchange

1001 - 5000 employees

Founded 2011

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

Kraken Digital Asset Exchange is a cryptocurrency platform that facilitates the buying and selling of over 200 cryptocurrencies, including Bitcoin, Ethereum, and many others. Founded in 2011, Kraken provides a comprehensive suite of features for both beginner and advanced traders, such as advanced trading interfaces and margin trading. The platform emphasizes industry-leading security, deep liquidity, and 24/7 customer support, making it a trusted choice for users worldwide. Kraken caters to individual investors as well as institutional clients, offering services like OTC trading and custody. The company is committed to transparency with its proof of reserves and mission-driven values. Kraken operates globally, supporting clients in over 190 countries, with a quarterly trading volume exceeding $207 billion. However, users are advised of the high risk of crypto investments and the lack of regulation in some jurisdictions.

📋 Description

• 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

🏖️ Benefits

• Wellness allowance • Medical insurance • Dental insurance • Vision insurance • 401(k)

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