Number of positions: 1
Date for this role: Until 10/31/2022
Extension: Yes, based on funding source
Full time permanent position: Possible
The schedule hours: Mon- Fri 9-5
Location: WFH – Toronto
Story behind the need
Org Unit – Global Data & Analytics Solutions
Project: Additional workload.
The main function of the Data Engineer is to develop, evaluate, test and maintain architectures and data solutions within our organization. The typical Data Engineer executes plans, policies, and practices that control, protect, deliver, and enhance the value of the organization’s data assets. Capability to architect highly scalable distributed data pipelines using open source tools and big data technologies such as Hadoop, HBase, Spark, Storm, ELK, etc.
• Design, construct, install, test and maintain highly scalable data management systems.
• Ensure systems meet business requirements and industry practices.
• Design, implement, automate and maintain large scale enterprise data ETL processes.
• Build high-performance algorithms, prototypes, predictive models and proof of concepts.
Skills: Must have
2+ years of experience as a Data engineer or related field
• 2+ years of hands on experience with ETL, ETL pipelines
• Collaborate with data architects, modelers and IT team members on project goals.
• Hands-on experience with HDFS, MapReduce, YARN, Pig, Hive, HBase, Zookeeper, Oozie
• Hands-on experience Python OR Scala.
Nice to have:
Experience with Airflow, Kubernetes
• Spark, Spark Streaming
• Ability to work as part of a team, as well as work independently or with minimal direction.
• Excellent written, presentation, and verbal communication skills
• Bachelor's degree in a technical field such as computer science, computer engineering or related field required.
2 step interview
1 interview, 45 minutes video conference with HM & Technical Data Engineer (Technical and behavior questions)
2 interview, 30 minutes video conference with HM (Technical and behavior questions)