Database System Principal Engineer
Crunch.io - Palo Alto, CA

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We are building the world’s first truly collaborative analytic platform. We are a top-notch team of statisticians, data analysts, and engineers with proven experience in delivering fast, accurate, compelling insights from large datasets. Now we are taking that experience to the cloud.

Our approach is new, but builds on the shoulders of giants. We value the many decades of data research, both academic theory and commercial experimentation. We value the contributions of our individual employees just as much. We’re looking for people who want to advance the possible as well as the practical, by delivering results our customers never imagined could be achieved so delightfully and effortlessly.

To provide that experience, we work hard so others don’t have to. But we’re not a cubicle farm or a sweatshop. We like to have the kind of fun that can only be attained through a team of smart people working together to achieve great things.

To apply, send your resume to bob@crunch.io.

Job Description This is an extremely rare opportunity to design and build a cutting-edge analytic database engine. You will take our prototype in-memory, column-oriented database from “should” to “does”, turning terabytes of data into rapid insights, advancing the state of the art in database theory and practice as you build.

Responsibilities
  • Develop and implement core database engine architectural improvements.
  • Work closely with statisticians and engineers to optimize analytic query workloads.
  • Design, develop, implement, and optimize storage and retrieval systems.
  • Qualifications This position will have a large impact on our business. We are looking for someone to join our founding team who will invest in their own future with quality work at this critical first stage. There may be 100 people in the whole world with the understanding and skill set to pull this off. Are you one of them? If so, where you live is not a factor; we have lots of proven experience with distributed teams.

    Education and Training
  • Master’s degree, or equivalent, in Computer Science, Engineering, Statistics, or related academic field.
  • Knowledge and Experience (required)
  • Data structures, algorithmic complexity and efficiency.
  • Strong knowledge of database theory and history, with a thirst for more.
  • High performance Python: multithreading and multiprocessing, optimization techniques, memory management, execution internals.
  • A history of relentless testing.
  • Knowledge and Experience (bonus)
  • C.
  • Column-oriented database internals, especially experience with MonetDB, SciDB, ParAccel, Greenplum, Vertica, HANA, or similar.
  • Network protocol design and optimization.