Data Platform Engineering Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and expand a team of senior data platform engineers focused on developing Kraken's real-time streaming infrastructure.

• Take ownership of the architecture and roadmap for high-volume, low-frequency data systems, emphasizing data technologies such as Spark, Kafka, Iceberg, RisingWave, and Apache Flink.

• Design and manage scalable data architectures that cater to trading, risk, compliance, analytics, and various product teams.

• Promote the use of AI automation and intelligent workflows by automating data quality checks, orchestrating pipelines, detecting anomalies, and creating self-healing infrastructure.

• Collaborate with ML/AI, analytics, and product engineering teams to provide platform capabilities that enhance their productivity.

• Advance Kraken's data lake and warehouse architecture to seamlessly support both batch and streaming workloads.

• Establish the technical direction for the team, ensuring a balance between reliability, speed, and cost efficiency at scale.

• Recruit, mentor, and retain top-notch platform engineers; foster a culture of ownership and technical excellence.

⛳️ Requirements

• Over 8 years of experience in data engineering, platform engineering, or distributed systems, including at least 3 years in a managerial role.

• Expertise in building data lakes on AWS (e.g., Spark, Athena, Iceberg, Parquet, Presto), encompassing data modeling, best practices for data quality, and self-service tools.

• Extensive experience in building and managing real-time data solutions at scale, including Kafka, Spark Streaming, Debezium, and CDC pipelines.

• Proven capability to manage competing priorities across various stakeholder groups, aligning platform investments with the requirements of product, finance, compliance, analytics, and other departments.

• Excellent communication skills, able to articulate risks, trade-offs, and roadmap decisions to both senior technical audiences and non-specialist stakeholders.

• Experience in designing or implementing AI/ML-driven automation within data workflows, including pipeline orchestration, intelligent monitoring, automated remediation, or LLM-integrated tools.

• Proficient in Python, Scala, or Java within a production data platform environment.

• Strong understanding of cloud-native data infrastructure, preferably AWS (including Glue, Athena, S3, EMR, Lambda, or similar services).

• Successful track record of managing, recruiting, and developing high-performance remote engineering teams.

• Ability to translate a long-term platform vision into actionable quarterly roadmaps.

• Servant-leadership approach — you mentor, remove obstacles, and foster the growth of your engineers.

🏝️ Benefits

• Wellness allowance

• Medical insurance

• Dental insurance

• Vision insurance

• 401(k)