Data Platform Engineering Team Lead
Lead and develop a software engineering team responsible for a large-scale data platform supporting reporting, billing, experimentation, machine learning training, and revenue optimization. Define technical direction, architecture, and roadmap while remaining hands-on with technical reviews and data
Responsibilities
- Lead, mentor, and grow a software engineering team
- Define technical strategy, architecture, and roadmap for the data platform
- Own the reliability, scalability, and performance of data pipelines
- Partner with engineering, product, finance, and machine learning teams
- Drive adoption of modern data technologies and AI-powered engineering practices
- Review architecture, code, and technical designs
- Guide the evolution of the Spark SQL platform and shared data infrastructure
- Represent the team in architecture reviews, hiring, incident postmortems, and technical forums
Requirements
- At least 5 years of experience leading and managing software development teams
- At least 8 years of software engineering experience with Java or a similar object-oriented language
- Experience building and operating large-scale distributed systems in production
- Experience with 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
- Bachelor’s degree in Computer Science or equivalent practical experience
Nice to have
- Production experience with dbt, Airflow, StarRocks, or Druid
- Experience using AI agents to improve engineering productivity
- Familiarity with machine learning data pipelines
Benefits
- Hybrid work schedule with three days in the office
- Health benefits
- Fully stocked kitchen
- Gym partnerships, parking, and location-specific perks