AWS DevOps/MLOps Engineer - Mindteck
Plano, TX 10016
About the Job
What you'll do
What you bring
Job Description:
DXC is seeking a talented AWS DevOps/MLOps Lead to develop platforms for big data and data science on AWS. As models, apps, and data pipelines are created and operationalized, the bigdata and data science team requires engineers with understanding of cloud native technology to develop, manage, automate, and facilitate the operational capabilities of the big data and data science team.
Required Skills:
• Experience in AWS system and network architecture design, with specific focus on AWS Sagemaker and AWS ECS
• Experience developing and maintaining Client systems built with open source tools
• Experience developing with containers and Kubernetes in cloud computing environments
• Experience with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo)
• Design the data pipelines and engineering infrastructure to support our clients' enterprise machine learning systems at scale
• Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
• Support model development, with an emphasis on auditability, versioning, and data security
• Experience with data security and privacy solutions such as Denodo, Protegrity, and synthetic data generation.
• Ability to develop applications using Python and deploy to AWS Lambda and API Gateway
• Ability to develop Jenkins pipelines using the groovy scripting.
• . Good understanding in testing frameworks like Py/Test.
• Ability to work with AWS services like S3, DynamoDB, Glue, Redshift and RDS
• Proficient understanding of Git and version control systems
• Familiarity with continuous integration and continuous deployment.
• Develop the terraform modules to deploy the standard infrastructure.
• Ability to develop the deployment pipelines using the Jenkins, XL Release
• Experience in Python boto3 to automate the cloud operations.
• Experience in documenting technical solutions and solution diagrams
• Good understanding of the simple python applications which can be deployed as a docker container.
• Experiencing in creating workflows using AWS step functions
• Create the docker images using the custom python libraries.
Required Skills:
• AWS (experience mandatory): S3, KMS, IAM, EC2, ECS, BATCH, ECR, Lambda, Data Sync, EFS, IAM Roles, Policies, Cloud Trail, Cost Explorer, ACM, AWS Route53, SNS, SQS, ELB, CloudWatch, Lambda and VPC, Service Catalog
• Automation (experience mandatory): Terraform, Python (boto3), serverless, Jenkins (Groovy), NodeJs
• Bigdata (Knowledge): Redshift, DynamoDB, Databricks, Glue, and Athena.
• Data science (Experience): Sagemaker, Athena, Glue, DynamoDB, Databricks, MWAA (Airflow),
• DevOps (experience mandatory): Python, Terraform, Jenkins, GitHub, Make files, and Shell scripting.
• Data Virtualization (Knowledge) : Denodo
• Data Security (Knowledge): Protegrity
Qualifications:
• Bachelor's degree from a reputed institution/university.
• 14+ years of building end-to-end systems as a Platform Engineer, Client DevOps Engineer, or Data Engineer.
• 4+ Years of experience in python, groovy, and java programming.
• Experience working in the SCRUM Environment.
While others say it, we do it: we care. We have great people and we do great work. Just as importantly, we have great relationships with an impressive clientele. Over 1,000 talented, diverse, and career-minded professionals are carving out their role and experiencing a good mix of challenges and opportunities – and we're rooting for them along the way, every day. For more, click: https://www.mindteck.com/career/life-at-mindteck.html
What you bring
Job Description:
DXC is seeking a talented AWS DevOps/MLOps Lead to develop platforms for big data and data science on AWS. As models, apps, and data pipelines are created and operationalized, the bigdata and data science team requires engineers with understanding of cloud native technology to develop, manage, automate, and facilitate the operational capabilities of the big data and data science team.
Required Skills:
• Experience in AWS system and network architecture design, with specific focus on AWS Sagemaker and AWS ECS
• Experience developing and maintaining Client systems built with open source tools
• Experience developing with containers and Kubernetes in cloud computing environments
• Experience with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo)
• Design the data pipelines and engineering infrastructure to support our clients' enterprise machine learning systems at scale
• Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
• Support model development, with an emphasis on auditability, versioning, and data security
• Experience with data security and privacy solutions such as Denodo, Protegrity, and synthetic data generation.
• Ability to develop applications using Python and deploy to AWS Lambda and API Gateway
• Ability to develop Jenkins pipelines using the groovy scripting.
• . Good understanding in testing frameworks like Py/Test.
• Ability to work with AWS services like S3, DynamoDB, Glue, Redshift and RDS
• Proficient understanding of Git and version control systems
• Familiarity with continuous integration and continuous deployment.
• Develop the terraform modules to deploy the standard infrastructure.
• Ability to develop the deployment pipelines using the Jenkins, XL Release
• Experience in Python boto3 to automate the cloud operations.
• Experience in documenting technical solutions and solution diagrams
• Good understanding of the simple python applications which can be deployed as a docker container.
• Experiencing in creating workflows using AWS step functions
• Create the docker images using the custom python libraries.
Required Skills:
• AWS (experience mandatory): S3, KMS, IAM, EC2, ECS, BATCH, ECR, Lambda, Data Sync, EFS, IAM Roles, Policies, Cloud Trail, Cost Explorer, ACM, AWS Route53, SNS, SQS, ELB, CloudWatch, Lambda and VPC, Service Catalog
• Automation (experience mandatory): Terraform, Python (boto3), serverless, Jenkins (Groovy), NodeJs
• Bigdata (Knowledge): Redshift, DynamoDB, Databricks, Glue, and Athena.
• Data science (Experience): Sagemaker, Athena, Glue, DynamoDB, Databricks, MWAA (Airflow),
• DevOps (experience mandatory): Python, Terraform, Jenkins, GitHub, Make files, and Shell scripting.
• Data Virtualization (Knowledge) : Denodo
• Data Security (Knowledge): Protegrity
Qualifications:
• Bachelor's degree from a reputed institution/university.
• 14+ years of building end-to-end systems as a Platform Engineer, Client DevOps Engineer, or Data Engineer.
• 4+ Years of experience in python, groovy, and java programming.
• Experience working in the SCRUM Environment.
While others say it, we do it: we care. We have great people and we do great work. Just as importantly, we have great relationships with an impressive clientele. Over 1,000 talented, diverse, and career-minded professionals are carving out their role and experiencing a good mix of challenges and opportunities – and we're rooting for them along the way, every day. For more, click: https://www.mindteck.com/career/life-at-mindteck.html
Mindteck is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, status as a qualified individual with a disability, or any other trait protected by law.
Source : Mindteck
