Big Data CloudOps Engineer
Complex problems require the right expertise! Today, one of the biggest challenges lies in data storage and processing, across these three main domains (3Vs): Volume, Velocity and Variety.
At Xpand IT, the Big Data technological area develops and implements architectures and software solutions that represent the state of the art on capturing, ingesting, storing and managing critical data from huge clusters where the 3Vs are always present. As concerns technology stack, we take advantage of almost every state-of-the-art framework in Big Data ecosystem such as Spark, Kafka, Hive/Impala, Azure Data Services or MongoDB using Java and Scala as programming languages to interact with them.
As a Big Data CloudOps Engineer, you’ll play a vital role in several phases of the adoption of the Big Data platform in the Cloud context (Azure or AWS), participating in analysing, outlining and sizing distributed storage and/or computing systems, setup, upgrade, securitisation and tuning. For these critical systems, particular focus on performance and security is crucial, as well as implementing the best service development practices to serve as the basis for monitoring tools.
Usually, this role also works closely with the development teams in designing, developing and installing application solutions, processing and storage of large-scale data.
Your daily activities will include:
- Setting up / upgrading / securitising/tuning platforms on a large scale in critical, ephemeral and/or self-scaling environments on a Cloud provider
- Implementing security rules and policies on Cloud platforms
- Recommending and periodically updating the best practices for using Cloud services
- Configuring best practices for monitoring the infrastructure
- Analysing sizing requirements and ideal services for each project to be implemented
- Designing and developing new processes for better stability and performance maintenance of environments
- Developing integration or automation processes for Cloud deployments. Being able to turn to containerised environments on Kubernetes
- Participating and helping solve performance, scalability and security issues
// Stacks: Cloudera, Confluent, Azure Data Services, MongoDB, Kerberos ou Windows Active Directory
SKILLS YOU NEED TO HAVE
- MSc / BSc in IT and Computers, Information Systems or Computer Science
- Good knowledge of Linux operating systemsare valued
Good shell scripting knowledge is valued
- Knowledge of the objectives and terminology ofdistributed high-availability systems is valued
- Team player and problem-solving skills
- Good communication skills (written and spoken)
- Fluent English (written and spoken)
// Will be a nice plus if you have:
- Hands-on experience in setting up Spark, Hive or Apache Hadoop
- Hands-on experience with automation tools such as Ansible, Terraform or CloudFormation
- Curiosity about Big Data technologies such as Hadoop, Kafka, MongoDB
- Curiosity about Kubernetes and the various existing flavours Openshift, Rancher, AKS or EKS
- Curiosity about the Cloud services that make up Azure Big Data Stack or AWS Big Data Stack, such as Databricks, Azure Synapse or Amazon S3
// Learn more about Big Data area:
Pedro Martins, Big Data System Engineer
As a Big Data System Engineer, every day is challenging: between the clusters deployments from scratch and the optimization of distributed systems, it is absolutely crucial to have a deep understanding of the ecosystem’s multiple services, dealing with many different contexts.