Role
Senior Data Engineer
Who We Are
Our mission: making memorable outdoor experiences accessible to everyone.
Outdoorsy is the most trusted RV rental and outdoor experiences marketplace on the planet. We have grown from a lofty white-board idea in 2015, to over $525M in GMV and offices worldwide in the US, Canada, Australia, Europe and the UK. We’ve mobilized the 56+ million idle RVs and camper vans around the world to ensure everyone has the access, choice, and opportunity to safely spend more time outside.
Over 856,000 vacation nights were booked on Outdoorsy in 2019. 93% of reviewed Outdoorsy
bookings receive 5-star ratings. With over 600,000 families and adventure seekers—and 50,000
RVs, travel trailers, and campervans to choose from—that’s a lot of sunset selfies taken!
Our platform handles availability scheduling, payment processing, communication, insurance, GPS tracking and roadside assistance all built in. Our rapidly growing user base has taken us from the United States to Canada, Australia and New Zealand. Our engineering team is a small mighty group of self-starting developers who are motivated by making an impact on the lives of our users, both financially for our owners or experientially for our renters.
Who You Are
A hands-on self directed data engineer that has built and refactored code bases to follow best practices. You’re a stickler for proper architecture and you’re not afraid to voice your opinion if something isn’t designed properly - as Data Engineering is the eyes through which they see the product. Understanding the business need, securing the right data sources, designing usable data models, and building robust & dependable data pipelines are essential skills. You are constantly learning about new cloud computing frameworks and technologies. Scalability, stability and performance are always top of mind when building new functionality or reviewing requests from the team. You will belong to a centralized Data Science/Data Engineering team, and contribute to a variety of projects and technologies. Projects include product relevance, ML modeling, services, and more.
What You’ll Be Doing
Design, build and automate large scale, high-performance data processing systems (batch and/or streaming) to enable data science solutions, drive business growth and improve the product experience
Build extremely efficient and reliable data pipelines to move and transform data (both large and small amounts)
Design, and develop our data models for optimal storage and retrieval to meet critical product and business requirements
Build data domain expertise and own data quality for your areas
Partner with data scientists, engineers and product managers to define problem statements, collect data, and make recommendations
Use your data experience to educate your partners, identify and address gaps and inconsistencies in the existing logging and processes, and advance effective product solutions
Required Experience
Experience working in startup fast paced environments
4+ years of professional experience in custom ETL/data pipeline design, implementation and maintenance
Experience with AWS or GCP cloud technologies and services (experience with analytics services and data lake concepts are a plus)
Experience with large data sets, big data technologies (e.g. Spark)
Experience with streaming data processing methods and frameworks (e.g. Kafka or Kinesis)
4+ years of professional experience working with SQL and noSQL databases
Experience in at least one programming language (e.g. Python, Spark, Scala or Java)
Experience designing and deploying high performance systems with reliable monitoring and logging practices
Experience with notebook-based Data Science workflow
Experience with Git hygiene and comfortable with Github, including feature branches, pull requests, and code review
Creative problem solver who enjoys collaboration
Excellent communication skills, both written and verbal
Minimum BSc or equivalent in Computer Science, Math or other technical fields