At Shutterfly, we’re all about people — bringing them together, making them feel welcome, and connecting them to experiences. We make our customers’ memories last a lifetime by capturing, preserving, and sharing them through photography and personalized products. Through our family of brands, trend setting products, cutting edge technology, and best in class customer service, we help our customers, and each other, share life’s joy.
As part of the Data Engineering team you will tackle the scalability, performance and distributed computing challenges needed to collect, process and store data for a $2B customer eCommerce, images and customizable product business. You will enhance the Data Warehouse at Shutterfly on AWS, supporting the breadth and depth of the company’s analytic needs, including the BI, Data Sciences, Product Management, Product Marketing, CRM, and Machine Learning teams to deliver data innovations in our Websites and Mobile Apps.
The Data Warehouse, Platform and Infrastructure vision is to provide Shutterfly teams the ability to manage the full life cycle of their data at all levels, simplifying, commoditizing and democratizing its collection, computation and analytics through well-architected use of the AWS.
To apply for this role, we are looking for candidates with sound analytic, design and problem-solving skills, who have expertise with distributed and high-performance systems, service design and large-scale data ingress, egress and storage. Expertise with the AWS platform & Databricks is a big plus!What You'll Do Here:
The Skills You'll Bring:
- Own & build design, develop, test, deploy, maintain and enhance full-stack data engineering solutions for the Data Pipelines & Data Mart encompassing the Data Warehouse
- Provide technical leadership to both internal Data Warehouse team as well as to publishers & subscribers of the Shutterfly’s Enterprise Data Lake
- Identify, evaluate and evangelize through data-based evidence improvements to the Data Lake as we as the data processing environment; hence influence the data strategy
- With your technical expertise, own and manage project priorities, deadlines and deliverables
- Always with a customer focus, evangelize the benefits of existing solutions and new technologies to drive the use and push the technology of the Data Warehouse forward
- Work closely with Data Operations to improve CI/CD pipelines, as well as continually improve the operations, monitoring and performance of the Data Warehouse
- Work across multiple teams in high visibility roles and own solutions end-to-end
- Expert knowledge Python, Spark and SQL scripting, working knowledge of R or similar statistical computing packages.
- 10+ years of hands on experience in building data & feature engineering applications, including design, implementation, debugging, and support
- Deep understanding of data integration to support analytics & feature engineering for Machine learning algorithms
- Strong at applying data structures, algorithms, and object-oriented design, to solve challenging data integration problems
- Experience working in the AWS Services Ecosystem or relevant Cloud Infrastructures such as Google Cloud or Azure
- Experience with Databricks as a compute environment is a plus
- Bachelor’s / Master’s degree in Computer Science or equivalent