DevOps Engineer - Big Data

Here's some of what you'll be doing.

The ideal candidate is willing, and able to research, maintain, configure, administer, and provision infrastructure, applications, and services across our platforms.

• Configure, install, maintain and manage big data technologies including Hadoop, Hbase, Spark, Dremio, Kafka across multiple environments
• Develop and maintain scalable and efficient automation solutions for data stack operations, preferrably using SaltStack (SALT) or other automation tools
• Implement monitoring solutions to track performance of data stack - identify and reoslve performance bottlenecks for high availability and reliabilityMPI does not discriminate on the basis of race, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, or based on an individual's status in any group or class otherwise protected under applicable human rights legislation.

MPI encourages applications from minorities, women, the disabled and all other qualified applicants

Here's some of what you'll bring to the table.

Must-have :

o Excellent problem-solving skills, engineering mindset (must be able to demonstrate this in interviews)

o strong experience with big data technologies (Hadoop, Hbase, Spark, Dremio, Kafka, etc)

o SaltStack (SALT) preferred for configuration management. Ansible, CHEF, etc. are also considered.

o Solid foundation in managing and troubleshooting Linux environments

o Configuration management tools e.g. SALT, Ansible or CHEF

o Development / Engineering experience e.g. Java, C#, .NET, Shell, Python

o Jenkins, Github, Bitbucket, Nexus or similar toolsets

o Database experience, relational and NoSQL databases

o Cloud experience e.g. AWS, GCP, Azure Services including IaaS, AKS, ADLS, ADF, Databricks, Blob, Event Hub and more

Nice to have :

o IaC tools e.g. Terraform, Azure ARM templates

o High-Performance Computing clusters (e.g. HPC Pack)

o Big data platform including but not limited to Hadoop, HDFS, HBase, Hive, Zookeeper, Kafka

o Veracode, SonarQube

o SOA, Microservices architecture

o Splunk, DataDog, ITRS, Sensu, Foglight, ELK

o AutoSys, ServiceNow, JIRA, Confluence

The capital markets division of a leading Canadian bank.

Great compensation and interesting technical work