Sysco (NYSE:SYY) is the global leader in selling, marketing and distributing food products to restaurants, healthcare and educational facilities, lodging establishments and other customers who prepare meals away from home. Its family of products also includes equipment and supplies for the foodservice and hospitality industries. With more than 57,000 associates, the company operates approximately 326 distribution facilities worldwide and serves more than 625,000 customer locations. For fiscal 2020 that ended June 27, 2020, the company generated sales of more than $52 billion.
Sysco LABS supports Sysco’s digital transformation with engineering teams in Colombo, Sri Lanka, and Austin and Houston, Texas, in the USA. Operating with the agility and efficiency of a tech–startup and backed by the domain expertise of the industry leader, Sysco LABS’ mission is to support the innovation of Sysco’s business across the entire foodservice journey.
We are currently on the lookout for a Data Engineering Lead / Senior Data Engineer / Data Engineer
- Drive the digital transformation of a global company with specific focus on large scale data streaming and optimal mixing of traditional and modern technologies within this realm.
- Provide inspirational leadership to a team towards building the foundational data layer.
- Mentor less experienced developers on engineering best practices and leveraging cloud technologies to handle big data.
- 3+ years of demonstrated work experience with streaming technologies such as Kinesis and Kafka (Confluent/Apache), and experience with KSQL, cluster management and data streaming solution architectures.
- Design and implementation experience of streaming solutions over legacy platforms (AS400, Oracle) and SAAS providers such as SFDC and Workday.
- Experience working with large analytical/relational/No-SQL datasets (~50 TB) on top of services and technologies such as Redshift, DynamoDB, MongoDB and Postgres to help design scalable ETL processes (batch/streaming) with complex data transformations, error handling and monitoring.
- Experience working within container environments in AWS ECS and EKS.
- Experience writing well-tested code (unit, integration, functional, automation), proper deployment practices (CI/CD – Jenkins etc.) and working in an environment with robust coding standards and strict code/design review processes.