Data Platform Engineering Team Leader

Requirements:
5+ years leading and managing software development teams.
8+ years of software engineering experience with Java or a similar object-oriented language.
Experience building and operating large-scale distributed systems in production, including Kafka, Spark, Linux, and Kubernetes.
Strong understanding of object-oriented design, concurrent programming, SQL, and NoSQL databases.
Experience leading architecture discussions, reviewing code, and driving technical direction across engineering teams.
B.Sc. in Computer Science or equivalent practical experience.
Bonus points if you have:
Experience with dbt, Airflow, StarRocks, or Druid in production.
Experience leveraging AI agents to improve engineering productivity and familiarity with ML data pipelines.
How youll make an impact:
Lead, mentor, and grow a team of talented software engineers while fostering technical excellence and ownership.
Define the teams technical strategy, roadmap, and architecture for one of our companys core data platforms.
Own the reliability, scalability, and performance of the data pipelines powering reporting, billing, experimentation, and ML training.
Partner with engineering, product, finance, and ML teams to align priorities and deliver high-impact platform capabilities.
Drive the adoption of modern data technologies and AI-powered engineering practices to improve developer productivity and platform evolution.
Stay hands-on by reviewing architecture, code, and technical designs, while helping the team solve complex engineering challenges.
Guide the evolution of the Spark SQL platform and shared data infrastructure used across R&D.
Represent the team in architecture reviews, hiring, incident postmortems, and technical forums.