Data Engineer


We are looking for a Data Engineer (BIE) with strong analytical, communication and project management skills to join our team. Working closely with business stakeholders and senior leadership, you will help identify and solve complex language and currency problems and develop metrics and reports to measure our impact on our business. In a typical day, you will work closely with the product management team, retail teams, machine-learning scientists, statisticians, software engineers, and various business groups.

About you:
You're looking for a career where you'll be able to build, to deliver, and to impress. You look at problems holistically and thrive on the intricate complexity of designing feedback loops and ecosystems. You want to work on projects where you are implementing solutions to real problems that require creative solutions and deep understanding of the problem space.

You challenge yourself and others to constantly come up with better solutions. This highly visible role requires frequent communication with senior leadership in order to help shape and deliver on the product roadmap and requires you to nimbly switch between strategic and tactical initiatives to achieve technical, business, and customer experience goals. You'll be given the unique opportunity to own and drive initiatives across the Our Retail as a whole -- from algorithmic innovation, all the way down to the datasets that the back-end services consume.

About us together:
We're going to change the way that Our thinks about supporting our global customer. Along the way, we're going to face seemingly impossible problems. We're going to argue about how to solve them, and we'll work together to find a solution that is superior to each of the proposals we came in with. We'll make tough decisions, but we'll all understand why. We'll be the dream team.

The ideal candidate for this space will be highly quantitative, have great judgment, strong data mining and modeling skills and is comfortable facilitating ideation and working from concept through to execution. You will have demonstrated an ability to manage and develop medium to large-scale data tables, identify requirements and build financial reporting and planning models and tools that are statistically grounded but also explainable operationally, apply technical skills allowing the models to adapt to changing attributes, optimize forecast accuracy and to better understand and mitigate model variance drivers. In addition to building data tables, modeling and technical skills, you will possess strong written and verbal communication skills, strong focus on internal customers and professional demeanor and high intellectual curiosity with ability to learn new concepts and frameworks, algorithms and technology rapidly as changes arise.

Some problem spaces we'll be working on:

DATAMART - as we release new languages across marketplaces, our business teams will want to understand customer trends and interactions with these new marketplaces. Ideally, we want to enable our business teams to report on the various languages within a marketplace as if those languages were individual businesses. As such, we need to create a DataMart that enables all business metrics to be split by language and also enables business users to execute ad hoc queries to answer questions that we have not currently considered. As we create the DataMart, we will have to consider the scale of data that we will be handling (at the scale of our global retail business) and employ Bigdata techniques to aggregate and manipulate this data. We will need to design the platform to be robust and to seamlessly recover from disaster, should the need arise. Consistency and validation will be primary concerns as we understand that systems fail, specifically systems upon which we rely for signal and we need to protect our business teams from making decisions based upon incomplete information.

CUSTOMER EXPERIENCE - as arbiters of the customer experience, we need to understand our customers' experience in their languages of preference. Similarly, given the scope of this initiative, it is clear that we will not be able to translate all content in a single release. As a result, it is critical that we can truly measure the customer experience as a function of our translations (both coverage and quality) throughout their journey within the Our marketplace. This is further complicated by the fact that our customers receive a unique experience based upon their browse history, so our method of measurement must be considerate of and support such a dynamic experience. Furthermore, in real time and with zero latency, we want to understand when the experience is broken so that we can take appropriate actions. This is going to be a challenge that may make use of the latest Bigdata streaming technologies to provide a real-time data and measurement pipeline.

You may already know if you're a fit, but perhaps you're worried about technology and experience requirements? Don't be - we're looking for smart, proven, engineers; if you're the right candidate, we're flexible.


· BS or MS in a quantitative field such as Mathematics, Statistics, Physics, Engineering, Computer Science or Economics
· Industry experience as a Data Engineer or related specialty (e.g. Software Engineer or Data Scientist) with extensive professional experience and a proven track record in a role focused on understanding, manipulating, processing and extracting value from large datasets.
· Experience processing, filtering, and presenting large quantities (Trillions of rows) of data
· Able to write optimize SQL scripts and build scalable data pipelines
· Excellent communication skills and the ability to work well in a team.
· Effective analytical, troubleshooting and problem-solving skills.


· Experience in Statistical Software such as R, SAS, SPSS, MINITAB
· Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL)
· Experience using one or more or: Python, VBA, MATLAB, Java, C++