Level: Expert

Location: San-Mateo, California

Employment Type: up to 6 month contract

What's the job:

Working as an expert adviser introducing mastery and best practices in Big Data platform design through a set of specific exercises for a small team of senior data engineers.

Responsibilities:

  • Work as an expert adviser together with Slice senior engineers on designing and prototyping:
    • near-real time ETL data pipeline for both immutable and mutable data
    • change management and information discovery in data lake
    • Slice data platform for machine learning infrastructure
  • Upon completion of the three conceptual researches mentioned above (the list can be extended or changed), work on general concepts of Slice AWS-based data platform together with Slice data engineers
  • Be a mentor, advise on best practices and standards to Slice data engineers

 Requirements:

  • Be an expert in applying AWS infrastructure (S3, Kinesis, EMR, Redshift, Glue, Lambda, Athena, Spectrum, SageMaker, etc.) to the design and development of Big Data platforms.
  • Love to be a mentor

Who we are:

Slice is online shopping, smarter. Slice is transforming online shopping and retail by unveiling never-before-seen digital commerce data via its e-commerce intelligence products, APIs, and consumer applications.

Slice operates a market research company, Slice Intelligence. With the world’s largest panel of online shoppers, only Slice offers vital intelligence that is the pulse of the digital economy—actual purchases directly from online shoppers, on any device or location, reported daily. Learn more about Slice Intelligence at www.sliceintelligence.com and on twitter @SliceIntel.

Slice is an independent, wholly-owned subsidiary of Rakuten. Slice was founded by proven entrepreneurs and offers the best of both worlds: a start-up with the backing of an established global company that is revolutionizing the internet services landscape, Rakuten.

Slice was incubated as a research project at Stanford, where the best and brightest minds in machine learning set forth on how to extract business value from the vast amount of unstructured purchase data in inboxes. When we took that project out of the lab and to the market, we retained the culture of excellence and personal growth, with respect for a healthy work-life balance. Because we love what we do and care about the people we work with.

Values:

  • Start­Up Environment – Work is fun, roles are challenging. Always prioritize the company’s success over egos. We innovate, take risks, move quickly and fail fast.
  • Hire smart and develop talent – ­ We are entrepreneurial self-starters who ignite/inspire growth on an individual, team and company level.
  • Say it like it is – We create a transparent, respectful environment within our company and for our users and partners. We give and receive prompt honest feedback.
  • Get it done ­ – We measure our success based on results rather than activity. We use the 80/20 rule. ­Perfect is the enemy of good.
  • Customer success is our own – We treat our customers and partners with respect. We are easy to do business with.