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Databricks

Sr. Staff Software Engineer - Managed Tables

Posted 14 Days Ago
Be an Early Applicant
In-Office
Mountain View, CA, USA
229K-314K Annually
Senior level
In-Office
Mountain View, CA, USA
229K-314K Annually
Senior level
As a Sr. Staff Software Engineer, you will optimize large-scale distributed systems, deliver scalable architectures, debug, mentor engineers, and drive technical projects across teams.
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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. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. 

The ManagedTables team at Databricks is responsible for the DataIntelligence initiatives that underpin the Unity Catalog ManagedTables offering. This encompasses products such as Predictive Optimization, Liquid Clustering, and control plane services facilitating Unity Catalog and Iceberg Rest Catalog API-based access to ManagedTables. The team is accountable for optimizing exabytes of data and saving millions of dollars annually for our customers through the Data Intelligence offerings.

As part of this team, you will be working on realizing enterprise grade autonomous analytical datasystems - that ensure the best performance out-of-the-box. You will design and implement these next gen systems that leapfrog state-of-the-art:

  • Storage lifecycle and additional background optimizations for a knob-free experience via Predictive Optimization
  • Efficient storage structures and innovations to power storage layout solutions for the ML world
  • Influence the Data format and Catalog interface unification efforts and enable strong ecosystem interoperability for ManagedTables

The Impact you will have:

  • Solve real business needs at large scale by applying your software engineering experience and by driving strong collaboration with Product partners
  • Deliver a highly scalable, available, and inter-operable architecture for Managed Tables.
  • Low level systems debugging, performance measurement & optimization on large production clusters.
  • Build architecture design, influence product roadmap, and take ownership and responsibility over new projects.
  • Introduce tools to allow greater automation and operability of services.
  • Use your deep experience to help prevent and investigate production issues.
  • Plan and lead complicated technical projects that work with several teams within the company.
  • Mentor and up-level engineers on the team

What We’re Looking For:

  • 15+ years industry experience building and supporting large-scale distributed systems.
  • A passion for database systems, storage systems, distributed systems, language design, or performance optimization
  • Experience working towards a multi-year vision with incremental deliverables
  • Motivated by delivering customer value and impact.
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Experience driving company initiatives towards customer satisfaction.
  • BS/MS/PhD in Computer Science or related majors, or equivalent experience.


Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected 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 anticipates utilizing 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.


Local Pay Range
$228,600$314,250 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

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.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Databricks San Francisco, California, USA Office

160 Spear Street, San Francisco, CA, United States, 94105

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