Data Platform Engineering Manager
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About this role
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 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 grow your engineers
AI-ready to 10X the team efficiency and overall output.
Nice to haves
Experience with RisingWave and/or Clickhouse specifically — either in production or in serious evaluation
Familiarity with LLM-based agents or AI workflow frameworks (e.g. LangChain, LangGraph, custom orchestration)
Background in cryptocurrency, trading systems, or high-throughput financial data
Experience building self-service data platform tooling for internal engineering consumers
Contributions to open-source streaming or data infrastructure projects
Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis.
Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution.
We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Our commitment
Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto.
We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision.
As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws.
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