At Canva, we work every day to make a significant positive impact on society. Our mission is to democratise design and empower creativity for anyone and everyone, on every platform!
Since launch in April 2013 we have grown exponentially, amassing over 20 million users in over 100 languages. We are one of the world’s fastest growing technology companies with software engineering being the core part of who we are.
As a Data Engineer at Canva, you will be building out the infrastructure to support the efforts of the Data Science and Data Analytics capability across the entire business - ensuring we continue to deliver business value and rich features and functionality to our millions of users around the world.
Some of the technologies in our environment include Python, Docker, Scala, Spark, Java (when we interact with the application repository), Terraform, Kubernetes, and Argo. You'll also be heavily exposed to the tools we use within AWS, including Elastic MapReduce (EMR).
- Designing, building, future-proofing and operating large scale data infrastructure in production (performance, reliability, monitoring)
- Thinking through long-term impacts of key design decisions and handling failure scenarios
- Responsibility for the continued development of new features, functionality, and optimization from raw data ingestion, to the access and serving layers
- Responsibility for the delivery of Data projects from inception to deployment across a wide range of initiatives across the business; in conjunction with Growth, Experiments, Analytics, and the Data Science Team
Required Experience & Skills
- Strong software engineering skills; ideally not constrained to a particular area of our stack but rather able to navigate it wholistically
- Strong understanding of Computer Science/Engineering fundamentals and first principles covering: non-trivial system design, concurrency, multithreading, data structures, architecture, and various design patterns
- Advanced coding proficiency in Java (Python, Scala, C#, or C++ experience is great
- Experience writing MapReduce and/or Apache Spark jobs in a high load production environment
- An understanding of distributed data processing methodologies, frameworks, and best practices
- An understanding of the broader Hadoop and Big Data ecosystem – tools such as Presto, Airflow, Luigi, etc
- Experience working in cloud-hosted Linux environments (AWS, Google Cloud, Azure)
- Solid understanding of databases with solid working knowledge of SQL
- Clear communication skills and ability to work cross-functionally across the business
- Competitive salary, plus stock options via our ESOP plan
- Flexible daily working hours, we value work-life balance
- Breakfast and lunch prepared by our wonderful Vibe team
- Onsite-Gym and Yoga Membership
- End-of-Trip Facilities: Bicycle parking and showers
- Generous parental (including secondary) leave policy
- Pet-friendly offices
- Sponsored social clubs, team events and celebrations
- Relocation budget for interstate or overseas individuals (see below for visa information)