Data Platform Engineering Manager
Payward, Inc. is a global financial infrastructure company and the parent organization behind Kraken. It provides trading, custody, payments, lending, staking, tokenized assets, derivatives, and market data infrastructure to consumers, professional traders, institutions, enterprises, fintechs, banks, exchanges, asset managers, and onchain platforms.
Funding history
Investors
Projects
About Payward, Inc.
Payward, Inc. operates a unified financial infrastructure platform powering a portfolio of products including Kraken, NinjaTrader, Breakout, xStocks, CF Benchmarks, and Payward Services. Its shared architecture provides global liquidity, risk and margin management, collateral and settlement, compliance and licensing, and operational infrastructure across crypto, tokenized assets, and traditional markets. Through Payward Services, the company offers APIs and infrastructure for crypto trading, custody, on/off-ramps, tokenized equities, derivatives, staking and yield, payments, and benchmark data. Payward operates across more than 190 jurisdictions and serves consumers, professional traders, institutional investors, enterprises, fintechs, banks, exchanges, asset managers, and DeFi/onchain protocols.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead and grow a team of data platform engineers, own the architecture and roadmap for real-time streaming systems, drive AI-powered automation, evolve lake and warehouse architecture, set technical direction, and hire, mentor, and retain engineers. You will align platform investments with stakeholder needs and turn long-term vision into quarterly roadmaps.
Requirements
- 8+ years in data engineering, platform engineering, or distributed systems
- At least 3 years managing engineering teams
- AWS data lake experience
- Data modeling and data quality practices
- Real-time data at scale
- Kafka, Spark Streaming, Debezium, and CDC pipelines
- Stakeholder management
- Communication skills
- AI or ML-powered data workflow automation
- Python, Scala, or Java
- Cloud-native data infrastructure
- Remote engineering team management
- Recruiting and developing engineers
- Quarterly roadmap planning
- Servant leadership
Responsibilities
- Lead and grow a team of senior data platform engineers
- Own the architecture and roadmap for real-time data systems
- Design and operate scalable data architecture
- Drive AI automation and intelligent workflows
- Partner with ML, AI, analytics, and product engineering teams
- Evolve data lake and warehouse architecture
- Set technical direction
- Hire, mentor, and retain platform engineers
- Manage stakeholder priorities
- Translate platform vision into quarterly roadmaps
