Data Platform Engineering Manager

Kraken; Brasil; Híbrido; BRL 279 000 - 390 600; Tempo integral

Resumo da oferta

Kraken is hiring a lead for its Data Platform team in Brazil, responsible for implementing a high-performance real-time data streaming infrastructure. The successful candidate will have over 8 years of experience in data and platform engineering, manage a talented team, and design scalable architectures for diverse product teams. Key technologies include Spark, Kafka, and AWS infrastructure. Kraken emphasizes a culture of mentorship and technical excellence within remote teams.

Qualificações

• 8+ years in data engineering or platform engineering, with 3+ years managing teams.
• Strong expertise in building real-time data systems at scale.
• Proficiency in Python, Scala, or Java for data platforms.

Responsabilidades

• Lead a team for Kraken's real-time data platform.
• Design scalable architectures for trading and analytics.
• Drive AI automation for data quality and pipeline efficiency.

Conhecimentos

Data engineering

Platform engineering

Distributed systems

Team management

Real-time data

AI/ML workflows

AWS

Communication

Python

Scala

Java

Ferramentas

Kafka

Spark

Debezium

RisingWave

Clickhouse

Descrição da oferta de emprego

Kraken's Data Platform team builds the real-time infrastructure that powers decision-making across one of the world's largest digital asset exchanges. 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.

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 serves 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

Skills You Should HODL

• 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.

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.

We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments are designed to evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Assessment results are considered alongside other relevant information, such as 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 that’s 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.