Data Platform Engineering Manager

Kraken Digital Asset Exchange

Data Platform Engineering Manager leading a team in building real-time streaming infrastructure at Kraken. Owning architecture and fostering AI-driven automation for data systems.

Posted 4/24/2026full-timeRemote • 🇺🇸 United StatesSeniorLead💰 $110,400 - $220,800 per yearWebsite

Tech Stack

Tools & technologies

ApacheAWSCloudDistributed SystemsJavaKafkaPythonScalaSpark

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringplatform engineeringdistributed systemsdata-lakesdata modelingdata qualityreal-time datapipeline orchestrationPythonScala

Soft Skills

team managementcommunicationstakeholder alignmentservant leadershipmentoringtechnical excellenceownershipprioritizationcoachingproblem-solving