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Data Platform Engineering Manager
Skills
AdoptionApache SparkApache Spark StreamingContextGlueInfrastructure ProjectsModeling
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 8+ years in data engineering platform engineering or distributed systems
- At least 3 years managing engineering teams
- Experience building data lakes in AWS with Spark Athena Iceberg Parquet and Presto
- Strong expertise in real-time data at scale including Kafka Spark Streaming Debezium and CDC pipelines
- Proven ability to manage competing priorities across multiple stakeholder groups
- Strong communicator able to explain risks trade-offs and roadmap decisions
- Experience designing or adopting AI ML powered automation in data workflows
- Proficiency in Python Scala or Java in a production data platform context
- Solid understanding of cloud-native data infrastructure with AWS preferred
- 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 with coaching and unblocking engineers
Nice to have
- AI-ready
- Servant leader
- Strategic thinker
- Cross-functional
- Mentoring focus
Day to day
- Lead and grow a team of senior data platform engineers building real-time streaming infrastructure
- Own the architecture and roadmap for high-volume data systems using tools like Spark Kafka Iceberg RisingWave and Flink
- Design and operate scalable data architecture that serves trading risk compliance analytics and product teams
- Drive adoption of AI automation and intelligent workflows across data quality pipeline orchestration monitoring and remediation
Hiring process
- Applications are accepted on an ongoing basis
- Candidates may complete job-related skills or work-style assessments
- Assessments are reviewed alongside experience and interviews