Engineering | Redwood City, CA, United States
The Data Engineer leads shopkick’s data collection and warehousing efforts. S/he owns the design and implementation of a data warehouse to store mobile usage, web site, and operational data, gathering data into the warehouse, and analysis of the data. The Data Engineer is an interdisciplinary individual who works closely with many stakeholders to ensure that the data most important to analyzing and improving shopkick’s operations is accessible and well-understood.
shopkick helps people live an affordable awesome life. It helps them save, find, discover and get rewarded at stores they already go to. All they need to do is show up!
shopkick is the most used shopping app at retail stores in the U.S. (Nielsen data), and a World Economic Forum Tech Pioneer. It has over 150 brand partners (P&G, Unilever, Mondelez, L’Oreal, Revlon, General Mills, Pepsi etc) and 15 retail partners (Target, Best Buy, Macy’s, Old Navy etc), and is deployed in over 10,000 large stores across the U.S. In 2013, shopkick drove $500M in revenue for its partners (2012 - $200M, 2011 - $110M). shopkick adds a digital layer on top of the physical store experience for over 7 million users, to make it personal and rewarding. In November 2013, shopkick launched the first Apple iBeacon-related live trial with a major retailer anywhere (Macy’s) with shopkick’s shopBeacon platform. This technology allows brands to connect directly with consumers in the store.
shopkick Starts 100-Store iBeacon Trial For American Eagle, Biggest Apparel Rollout Yet
Apple’s iBeacon Comes To Macy’s: Is This The Future of Shopping?
Macy’s Begins Pilot Test of Apple’s iBeacon In Flagship New York, San Francisco Stores
Apple’s iBeacon Potential Emerges in shopkick Macy’s Initiative
shopkick users have earned $25M in rewards, scanned 70M products, and viewed 4B offers
Role & Responsibilities:
- Design data warehouse and datamarts.
- Work with product teams to ensure that the requisite data is recorded, and to extract data incrementally from its sources.
- Work with business owners to identity and provide key metrics.
- Create ETL processes and ensure that data is properly stored.
- Design queries and analytic processes.
- Write/deploy web-based reporting tools allowing stakeholders to access data.
- Provide regular reports to company stakeholders.
- You have a “feel” for numbers, and a passion for achieving a quantitative understanding of complex interactions.
- You have a strong, detailed understanding of business requirements – numbers mean something to you.
- You apply a great deal of creativity to presenting complex quantitative information in a way that brings insights to the fore.
- You’re open to using unconventional tools and approaches. It doesn’t faze you that some data might come from a traditional SQL database, while other data might come from log files analyzed using Hadoop, or from third-party tools. You’re smart about using what is available, but able to roll your own.
- 5+ years of experience in engineering; BS CS/MIS or equivalent.
- Good working understanding of statistics.
- Deep experience in star schema design, ETL, and extracting data from obscure sources; expert-level knowledge of SQL.
- Experience with analysis package(s) and practices.
- Experience with large-scale web site analysis and/or advertising optimization strongly preferred.
- Experience working with open source software tools and stacks preferred.
- Experience with Map/Reduce framework(s) preferred.
- Expertise in Python is a plus.