Staff Data Engineer
The Data Engineering team at RetailMeNot is responsible for developing core datasets and for exposing data services consumed by product, data science and business teams. Daily, we collect approximately a terabyte of analytics events and process hundreds of terabytes of data. Our team works efficiently to deliver new features for real-time and batch processing services. We use primarily AWS cloud services and Kubernetes to build and deploy services quickly, at scale and with no downtime.
In this role, you will bring staff-level data engineering experience, working side-by-side with our Data Science team. You will design and create datasets and large scale services for serving data. You will have exposure to a wide breadth of applications that will challenge you to balance specific consumption patterns against broader architectural concerns.
Do you love solving big data challenges that directly impact the success of products and deliver business results? If yes, come work with us to build world class data platforms!
Who You Are
- You have at least 7+ years of Data & Software developer experience
- You have experience developing production datasets and services at scale
- You have a point of view on the technologies we are currently using: Spark, Athena, Kinesis, AWS Lambda, Cloudwatch, Sentry, Luigi, PagerDuty, Redshift, Python, Kubernetes and experience building on some
- You have an evolved sense of test and validation practices in a modern data architecture
- You are familiar with common patterns, issues, limitations, and solutions that are seen when dealing with large datasets
- You show a proven understanding and application of computer science fundamentals: data structures, algorithms, and design patterns
- You are using AWS and are proficient with AWS services
- You have an ownership mentality and hold yourself accountable for your work
- You have great communication and collaboration skills
- CS Degree or equivalent field of study
What You'll Do
- You will contribute to a team responsible for serving reliable core data and data services at the company
- You will work with data science and data engineering to investigate how we can evolve our services to create new value for the product and business
- You will mentor developers on the team and in the engineering organization about data standard methodologies
- You will consistently improve maintainability and stability of our codebases and datasets
- You will research and recommend new technologies to enable us to iterate more quickly
Who We Are
- We have an open environment where engineers are given a lot of responsibility and the freedom to make a huge impact
- We have lots of intelligent people to work with and learn from
- We work on large scale challenges with a variety of technologies
- We have a great open vacation policy
- We'll provide you with food, food, and more food
- We believe in giving prizes, bonuses, and recognition for doing what you enjoy
Rewards
We offer an opportunity to be an integral part of a company that eagerly pursues disruption in its space to continue to drive innovation and lead the competition. Benefits of being an employee of RetailMeNot, Inc. include, but are not limited to the following:
- Competitive base & bonus packages; salary negotiable
- Long Term Incentive Plan
- Performance based rewards & recognition for your hard work and service
- Very competitive benefits packages, including best-in-class parental leave
- Open & flexible PTO
- Cell phone & gym membership reimbursements
- Fully stocked break room & onsite catered breakfasts & lunches multiple days/week
About Us
U.S. Equal Employment Opportunity/Affirmative Action Information
Individuals seeking employment at RetailMeNot, Inc. are considered without regards to race, color, creed, religion, gender, gender identity, national origin, citizenship, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, or any other protected classification. You are being given the opportunity to provide the following information in order to help us align with federal and state Equal Employment Opportunity/Affirmative Action record keeping, reporting, and other legal requirements.