Staff Backend Engineer, Data Analytics
- San Francisco, CA, USA
- Department: Engineering
Optimizely is the world's leader in customer experience optimization, allowing businesses to dramatically drive up the value of their digital products, commerce and campaigns through its best in class experimentation software platform. By replacing digital guesswork with evidence-based results, Optimizely enables product and marketing professionals to accelerate innovation, lower the risk of new features, and drive up the return on investment from digital by up to 10X. Over 26 of the Fortune 100 companies choose Optimizely to power their global digital experiences. Optimizely’s impressive customer list includes eBay, FOX, IBM, The New York Times and many more global enterprises.
At Optimizely, the Data Platform is the core foundation driving all our Experimentation and Personalization products. The Platform is leveraged across all product lines from spanning Analytics, Targeting, Recommendations and large-scale Ingestion. We are looking for a strong Backend Engineer to build cutting-edge Analytical capabilities on the Data Platform for our rapidly growing enterprise customer base.
Why is this exciting for you?
We have recently made a strategic bet on modern Data Science technical stack using Notebook technology as our next generation Analytical product offering. We are just getting started on this new, exciting Product and you’ll play a key role in influencing this Product’s roadmap and direction
- You will build highly scalable systems and services that ingest, deduplicate, count, aggregate, store, and archive these events as well as serve real-time analytics insights.
- You’ll be challenged to engineer solutions that need to work at enterprise grade for our customers that send us their user activity events at web scale (6B+ and multiple TB/day).
- The Analytics team works at the intersection of Distributed Systems and Applied Statistics so you’ll have a large scope of problem space to learn from and contribute to!
Team’s accomplishments and contributions:
- Our Streaming Analytics architecture in highscalability, one of the top sites for Distributed Systems architectures
- Our presentation at LinkedIn’s Stream Processing Meetup on our use of Samza for Sessionization:
- Our presentation in Apache Big Data Conference ‘17 in Miami on the use of a Lambda architecture with Streaming:
- Apache Samza Case Study of Optimizely’s Streaming use cases
- Our Engineering blog
- Bachelor's Degree or higher in Computer Science, or other technical field
- You have experience building data-centric applications in a web-scale environment with scale, operability, and performance in mind. You’ve built and deployed services on cloud infrastructure, like Amazon Web Services (AWS) or Google Cloud. Hands-on development and deployment experience with OSS like Apache Hadoop, HBase or Spark would be a big plus.
- Experience working on the modern Data Science technical stack is a big plus. E.g. Notebook technology (e.g. Jupyter, Zeppelin), Python.
- Strong interpersonal communication skills and ability to work well in a diverse, team-focused environment with other engineers, Product Managers, Site Reliability Operations etc.
At Optimizely, we embody inclusion and embrace diversity. We believe in work/life balance and bringing our true selves to work. To that end, we offer best-in-class perks and benefits that support our Optinauts along their career journey with us. Read more about our culture at optimizely.com/careers.
Optimizely is an equal opportunity employer and makes employment decisions on the basis of merit. Optimizely prohibits discrimination based on race, color, religion, sex, sexual identity, gender identity, marital status, veteran status, nationality, citizenship, age, disability, medical condition, pregnancy, or any other unlawful consideration. All your information will be kept confidential according to EEO guidelines.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.