Engineering Manager - Feature Store
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 an Engineering Manager for the Feature Store team, you will play a critical role in shaping and driving the future of our AI platform. The Feature Store is a key component of the Databricks data ecosystem, offering tight integration with the Unity Catalog, leveraging its governance, lineage, and semantics to unlock the full potential of the data for increased automation and model quality.
As an Engineering Manager, you will play a critical role in our team, steering the strategic direction and implementation of the Lakehouse AI Feature Store. Your insights and leadership will directly influence the way we handle, store, and leverage data for AI systems. This role is a unique opportunity for you to make your mark in a rapidly evolving field that blends technology, data science, and product innovation. In this role, you will work closely with cross-functional teams including Product, Design, and Go-To-Market teams to define the roadmap and deliver creative features that empower data-driven decision-making and accelerate AI development.
Key responsibilities include:
- Leading a talented engineering team to build both the product and infrastructure for Feature Engineering Platform, driving the adoption of the platform
- 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 Lakehouse platform while nurturing a thriving Python user base.
The impact you will have:
- Lead product development for one of the largest Feature Store / AI data management platform
- Define what a Data management platform looks like for the unstructured data and LLM space
- Grow a world-class team of software engineers working on AI data platform; manage a team of 7+ talented engineers
- Work closely with Product, Design, Field Engineering to understand customer needs and pain points, drive adoption of the product
- 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 related to ML Infra; experience on Feature Store is a plus
- Practical experience applying LLM/generative AI models
- A passion for database systems, storage systems, distributed systems, language design, or performance optimization; experience in managing distributed teams is preferred
- Can ensure the team builds high-quality and reliable infrastructure services; experience being responsible for testing, quality, and SLAs of a product; previous experience in building and leading teams in a complex technical domain such as distributed data systems or database internals
- Ability to attract, hire, and coach engineers who meet the Databricks hiring standards; can uplevel existing team via hiring top-notch senior talent, growing leaders, and helping struggling members; can gain trust of the team and guide their careers
- Comfortable working cross-functionally with Product Management and directly with customers; ability to deeply understand product and customer personas
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Databricks is the data and AI company. More than 9,000 organizations worldwide — including Comcast, Condé Nast, and over 50% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
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