Engineering Manager - PySpark

P-931 

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. 

As PySpark continues to gain traction within the open source Spark project and the Databricks Data Intelligence Platform, we're seeking a dedicated Engineering Team Lead to spearhead PySpark development initiatives, encompassing both open source and Databricks-specific components. Your primary mission will be to solidify Apache Spark's position as the go-to data processing framework within the Python community, while also using your expertise in Generative AI to make Spark more user-friendly and approachable, significantly expanding its user base. By providing innovative, industry-leading Generative AI-based user experiences for working with data, you will help Apache Spark gain Data+AI thought leadership in the open-source community.

The key responsibilities include:

• Leading a talented engineering team in PySpark development and promoting the adoption of Spark and the Databricks Data Intelligence Platform among Python users 
• Overseeing sustained recruitment of top-tier talent, fostering a well-organized and synergistic team structure, and collaborating effectively with internal and external stakeholders
• Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities
• Driving the integration of Generative AI into Spark to expand user base and improve user experience. 

By taking on this pivotal role, you will play an instrumental part in driving the success of Spark and the Databricks Data Intelligence Platform while nurturing a thriving Python user base.

The impact you will have:

• Lead product development for one of the fastest growing libraries in the open source Spark project, as well as the Databricks Data Intelligence Platform 
• Make company wide impact by driving Python adoption across the Databricks product portfolio
• Develop and deepen understanding and expertise in PySpark and PyData ecosystem, a well adopted yet still hyper-growing product
• Define, shape, and drive the future of Spark and Databricks Data Intelligence Platform  for Python users, aided by the power of Generative AI
• Grow a world class team of software engineers working on our compute fabric; increase headcount by 5+ engineers in next 18 months, with continued growth beyond that according to product objectives. Hire top-notch staff+ level talent
• Ensure consistent delivery against milestones and strong alignment with the field working "two-in-a-box" with product leadership
• Evolve organizational structure to align with long term initiatives, build strong "5 ingredient" teams with good comms architecture
• Manage technical debt, including long term technical architecture decisions and balance product roadmap

What we look for:

• 5+ years experience working in a related system, including ecosystem, Apache Spark and database internal
• Practical experience applying LLM/generative AI models
• A passion for database systems, storage systems, distributed systems, language design, or performance optimization
• Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and SLAs of a product. Previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals
• Ability to attract, hire, and coach engineers who meet the Databricks hiring standards. Can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members. Can gain trust of team and guide their careers. Experience managing distributed teams preferred
• Comfort working cross functionality with product management and directly with customers; ability to deeply understand product and customer personas