Data Platform Engineering Manager

Overview

In this role, you lead Kraken’s Data Platform team to design and scale real-time streaming and data infrastructure across trading, risk, compliance, and product domains. You own the architecture and roadmap for high-volume data systems and drive AI-powered automation to improve quality and reliability. You’ll partner with ML/AI, analytics, and product teams to accelerate data-driven decisions while evolving our data lake and warehouse. You’ll mentor engineers and shape a culture of technical excellence, ownership, and performance at scale.

Responsibilities

• Lead and grow a team of senior data platform engineers
• Own architecture and roadmap for high-volume data systems (Spark, Kafka, Iceberg, RisingWave, Flink)
• Design scalable data architecture serving trading, risk, compliance, analytics, and product teams
• Drive AI-powered automation and intelligent workflows (quality checks, orchestration, anomaly detection, self-healing infra)
• Partner with ML/AI, analytics, and product engineering to deliver platform capabilities
• Evolve data-lake and warehouse architecture for batch and streaming workloads
• Set technical direction balancing reliability, speed, and cost at scale
• Hire, mentor, and retain top-tier engineers; foster ownership and technical excellence

Key requirements

• 8+ years in data engineering, platform engineering, or distributed systems
• 3+ years managing engineering teams
• Experience building data-lakes in AWS (Spark, Athena, Iceberg, Parquet, Presto)
• Strong expertise in real-time data at scale (Kafka, Spark Streaming, Debezium, CDC)
• Ability to manage competing priorities across stakeholders
• Strong communicator for technical and non-technical audiences
• Experience designing/adopting AI/ML-powered automation in data workflows
• Proficiency in Python, Scala, or Java in production data platforms
• Experience with cloud-native data infrastructure (AWS Glue, Athena, S3, EMR, Lambda)
• Track record of managing and developing remote engineering teams
• Ability to translate long-term platform vision into executable quarterly roadmaps
• Servant-leadership style; coach and unblock engineers
• AI-ready to 10X team efficiency and output

• strong communication
• leadership and mentorship
• stakeholder management
• Spark
• Kafka
• Iceberg

…