data support engineer.

AWS Data EngineerRoles: Developer to Lead levelIT Experience range: 7+ yearsLocation: PAN India, Remote Skills and Experience: Must Have: Minimum of 2+ years in a solution architecture role OR Development using service and hosting solutions on AWS IaaS, PaaS and SaaS platforms. Good experience of AWS storage, and it's compute services.Good hands-on expertise on Python, SQL, PySpark, Hive and JenkinsAble to effectively use of AWS managed services (Step function, EMR, Lambda, Glue and Athena ) and design/develop data engineering solutionsExperience with analysis of requirement and client interaction.Good communication skills.Hands-on experience on developing Data platform and its components (Data lake, On cloud Datawarehouse, Batch and streaming data pipeline) Good to haveExperience with Databricks Basic understanding of data modeling Experience in migrating workloads from on-premises to cloud and cloud to cloud migrationsUnderstanding of Boto3 librariesExperience on AWS services like RDS, DynamoDB, RedshiftAbility to drive the deployment of the customers’ workloads into AWS and provide guidance, cloud adoption model, service integrations, appropriate recommendations to overcome blockers and technical road-maps for AWS cloud implementations. Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technologies.Basic understanding of sage maker and ML algorithmsAct as a subject-matter expert OR developer around AWS and become a trusted advisor to multiple teams. Coach and mentor engineers to raise the technical ability of the rest of the team, and/or to become certified in required AWS technical certifications Education: Graduate/post graduate in CSE/IT or related fields

Position QualificationsThe candidate should have a thorough interest and understanding of all aspects related to operation and support of Kubernetes and container technology, Azure cloud-based solutions in DevOps model, and strong scripting & automating skills. In order to ensure effective, stable and secure operation of DNV’s global Azure cloud IT infrastructure with on-premise elements, the key responsibilities for the GSS IT Kubernetes and DevOps Engineer are:Operation of Azure cloud-based servicesDeveloping and maintaining Kubernetes clustersScripting and automating (including integrations of cloud and on-premise components)React to customers’ feedback and requests using both ITIL and SCRUM methodologiesEnsure proper communication with customersIncidents troubleshooting and root cause analysisDevelopment of monitoring solution based on Azure Monitor toolsetCooperation with monitoring operatorsProducing design and operational documentationPosition QualificationsTo maximize your chances, you need:Strong knowledge and practical experience of Kubernetes Clusters and Container technology including:AKS, Docker, Helm, KustomizeService Mesh, networking, security toolsStrong operational knowledge of Microsoft Azure CloudOperational experience in DevOps toolchains and Infrastructure as Code tools including:Git, CI/CD pipelines – preferably Azure DevOpsTerraform, Terragrunt, Ansible, ARM templatesGitOps tools like ArgoCD or FluxKnowledge of monitoring toolset including Prometheus, Grafana and Azure Monitor suiteStrong scripting and automating skills using e.g. Bash, Python or PowerShellAny software development experience will be a plusLinux OS knowledgeFluent English in daily communication is required (both spoken and written);Experience in end-to-end project delivery with minimal supervision and documenting own work and processesUniversity education level requiredPersonal characteristics:Professional business communication skills (towards customers and stakeholders);Excellent interpersonal skillsSelf-motivatedEfficiency in daily workProactive and solution-oriented mindsetFlexibility and openness to changesResponsibility for own development and assigned tasks

Role: Datalake Engineer Must Have Skills : ADF, Azure Databricks Job Requirements: Datalake Engineer will work with multiple teams to deliver solutions on the Azure Cloud using core cloud data lakehouse tools (Azure Data Factory, Azure Databricks etc.) and to build the next generation of application data platforms (not infrastructure). Must be able to analyze data and develop strategies for populating data lakes. Should be able to develop complex coding using ADF or Spark framework.Key Requirement :Experience in Big Data components & azure Services such as  ADF, Kafka, Spark, Spark SQL, Dataframes etc.Good understanding of Azure Databricks platform and can build data analytics solutions to support the required performance & scaleAnalytical and problem-solving skills, particularly those that apply to a big data environment Technical Experience :Hands on knowledge on Azure Databricks (Read and write data in Azure Databricks)Azure Databricks integration with other servicesBest practices in Azure DatabricksHands on experience in SparkHands on experience on Azure Data Factory (ADF)Documentation expertise  Professional Attributes :Ability to organize and plan work independently Good written and verbal communication skills Good organization skills to balance and prioritize work, and multitask Good analytical and problem-solving skills to troubleshoot systems problems