Senior Engineering Manager - Data Lake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

Bellevue, WA - USA

• Lead a team of talented and high-performing engineers in the design, development, and support of highly distributed and scalable data platforms, with a specific focus on optimizing and enabling workloads on top of open table and open catalog formats like Apache Iceberg and Apache Polaris (incubating).

• Lead and participate in technical design and roadmap discussions relating to areas like Query Processing, Metadata Management, Performance, Scalability, and Open Source Interoperability

• Have direct ownership to grow a strategic and emerging part of Snowflake’s business to address new and expanding market opportunities in Data Lake and Data Analytics workloads

• Have direct impact on growth and development of your team through the full lifecycle of recruiting, hiring, mentorship, coaching, and identifying growth opportunities

• Demonstrate strong communication skills and the ability to work seamlessly across teams and organizations. Partner well with other leaders in the Engineering and Product organization on rhythms like annual & quarterly planning, staffing, project schedules, resource allocation, and more

• Be comfortable and effective in delegation - effectively leveraging Senior & Principal engineers to maximize your team’s impact

• Know when and how to shift resources across areas to achieve execution goals, while also ensuring effective ownership and longer-term alignment of work and skills

• Translate product requirements into engineering work for your team, partnering closely with peers in Product and other disciplines - to make our vision a reality!

• Use your strong technical foundation to set the bar for your team - build to last, deliver, and keep the quality exceptionally high!

• Foster a healthy and diverse team culture

• 7+ years industry experience designing and building distributed data systems, especially with a focus in database systems internals

• 3+ years of software engineering management experience.

• A track record of recruiting, leading, and growing high performing technical teams in a demanding talent market.

• Experience building enterprise grade software - reliable, secure, and trustworthy platforms and distributed systems at large scale

• Excellent problem solving skills, and strong CS fundamentals including data structures, algorithms, and distributed systems.

• Proven experience with authoring roadmap documents, project plans and RCAs.

• Fluency in Java or C++.

• Ability to work in a globally distributed team, collaborate well across disciplines, and mentor junior engineers.

• Excellent interpersonal communication skills. Outstanding written and oral English language skills.

• Bachelor’s Degree in Computer Science, Engineering, or equivalent

• Ability to work on-site in our Bellevue, WA or Menlo Park, CA office.

• Working with Apache open source projects and open data formats - Parquet, ORC, Avro - as well as with open table format standards - Apache Iceberg, Delta Lake

• Modern data analytics technologies such as Spark, Trino, Presto. Experience with query processing.

• Experience working and building on Data Catalog platforms, Metadata platforms, and Data Governance platforms, such as Unity, Glue, Nessie, Gravitino

• Working with or building Distributed Storage platforms such as AWS S3, Azure Blob Storage, Azure Data Lake Storage, Google Cloud Storage

• Internal design and implementation of query processing systems.