MetLife
Role Value Proposition
We are seeking a skilled Principal Data Platform Engineer with 5+ years of experience in designing, building, implementing, and managing data, analytics, and MLOps platform on Azure Cloud. Will be responsible for automating infrastructure, ensuring platform reliability, optimizing costs, and supporting data engineering, analytics, and machine learning workloads. Key Responsibilities Platform Architecture & Design: Design and architect scalable, secure, and cost-effective data, analytics, and MLOps platforms on Azure
Define cloud architecture patterns and best practices for data workloads
Create technical specifications and solution designs for complex cloud infrastructure
Evaluate and recommend new technologies and tools to enhance platform capabilities
Infrastructure Automation & Management: Implement Infrastructure as Code (IaC) using Azure Resource Manager (ARM), Bicep, or Terraform
Develop and maintain CI/CD pipelines for infrastructure deployment and application delivery
Automate provisioning and configuration management using tools like Azure DevOps, GitHub Actions, or Jenkins
Design and implement automated backup, disaster recovery, and high availability solutions
Data Platform Operations: Deploy and manage Azure data services including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Data Lake
Implement data governance, security, and compliance frameworks
Monitor and optimize data pipeline performance and resource utilization
Ensure data quality, lineage, and metadata management across the platform
MLOps Platform Development: Build and maintain MLOps infrastructure using Azure Machine Learning, MLflow, or similar platforms
Implement model deployment, versioning, and monitoring solutions
Develop automated ML pipeline orchestration and model lifecycle management
Ensure reproducibility and scalability of machine learning workloads
Security & Compliance: Implement security best practices including identity and access management (IAM)
Configure network security, encryption, and data protection measures
Ensure compliance with regulatory requirements (GDPR, HIPAA, SOX, etc.)
Conduct security assessments and vulnerability management
Cost Optimization & Performance: Monitor and optimize cloud resource costs through rightsizing and automation
Implement cost allocation and chargeback mechanisms
Performance tuning of data processing and analytics workloads
Capacity planning and resource forecasting
Collaboration & Support: Work closely with data engineers, data scientists, and analytics teams
Provide technical guidance and mentoring to junior team members
Participate in on-call rotation for platform support and incident response
Document processes, procedures, and system architecture
Essential Business Experience and Technical Skills
Required:
Bachelor's degree in Computer Science, Engineering, or related technical field, or 7+ equivalent professional experience will be considered
Cloud Platforms: 5+ years of experience with Microsoft Azure, including deep knowledge of Azure services (Azure SQL, Cosmos DB, Azure Data Factory, Synapse, Databricks, Data Lake, Machine Learning, etc.)
Infrastructure as Code: Proficiency in ARM templates, Bicep, Terraform, or similar tools
Containerization: Experience with Docker, Azure Container Instances, and Azure Kubernetes Service (AKS)
DevOps Skills
CI/CD: Strong experience with Azure DevOps, GitHub Actions, Jenkins, or similar platforms
Automation of infrastructure, application deployments using Azure DevOps Pipeline / Github actions.
Programming: Proficiency in Python, PowerShell, Bash, and/or other scripting languages
Monitoring & Logging: Experience with Azure Monitor, Log Analytics, Application Insights, or similar tools
Data Engineering: Knowledge of data pipeline orchestration tools (Databricks, Azure Data Factory)
Soft Skills
Excellent problem-solving and analytical skills
Strong communication and collaboration abilities
Ability to work in fast-paced, agile environments
Leadership and mentoring capabilities
Customer Service Orientation
Preferred:
Certifications
Microsoft Azure Solutions Architect Expert (AZ-305)
Microsoft Azure DevOps Engineer Expert (AZ-400)
Terraform Associate or Professional certification
Experience with multi-cloud environments (AWS, GCP)
MLOps
Experience with MLOps frameworks and tools (MLflow, Azure ML, Kubeflow
Understanding of machine learning lifecycle and model deployment strategies
GenAI exp. is preferred
Knowledge of data mesh and modern data architecture patterns
Data Technologies: Experience with SQL, NoSQL databases, data warehousing, and big data technologies
Security & Compliance: Strong understanding of cloud security principles and best practices
Experience with Azure Active Directory, RBAC, and identity management
Knowledge of data privacy regulations and compliance requirements
Experience with security scanning and vulnerability assessment tools
Experience with streaming data technologies (Apache Kafka, Azure Event Hubs)
Background in financial services, healthcare, or other regulated industries Experience with agile/scrum methodologies
At MetLife, we’re leading the global transformation of an industry we’ve long defined. United in purpose, diverse in perspective, we’re dedicated to making a difference in the lives of our customers. Equal Employment Opportunity/Disability/Veterans If you need an accommodation due to a disability, please email us at accommodations@metlife.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application process. MetLife maintains a drug-free workplace.
#J-18808-Ljbffr
We are seeking a skilled Principal Data Platform Engineer with 5+ years of experience in designing, building, implementing, and managing data, analytics, and MLOps platform on Azure Cloud. Will be responsible for automating infrastructure, ensuring platform reliability, optimizing costs, and supporting data engineering, analytics, and machine learning workloads. Key Responsibilities Platform Architecture & Design: Design and architect scalable, secure, and cost-effective data, analytics, and MLOps platforms on Azure
Define cloud architecture patterns and best practices for data workloads
Create technical specifications and solution designs for complex cloud infrastructure
Evaluate and recommend new technologies and tools to enhance platform capabilities
Infrastructure Automation & Management: Implement Infrastructure as Code (IaC) using Azure Resource Manager (ARM), Bicep, or Terraform
Develop and maintain CI/CD pipelines for infrastructure deployment and application delivery
Automate provisioning and configuration management using tools like Azure DevOps, GitHub Actions, or Jenkins
Design and implement automated backup, disaster recovery, and high availability solutions
Data Platform Operations: Deploy and manage Azure data services including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure Data Lake
Implement data governance, security, and compliance frameworks
Monitor and optimize data pipeline performance and resource utilization
Ensure data quality, lineage, and metadata management across the platform
MLOps Platform Development: Build and maintain MLOps infrastructure using Azure Machine Learning, MLflow, or similar platforms
Implement model deployment, versioning, and monitoring solutions
Develop automated ML pipeline orchestration and model lifecycle management
Ensure reproducibility and scalability of machine learning workloads
Security & Compliance: Implement security best practices including identity and access management (IAM)
Configure network security, encryption, and data protection measures
Ensure compliance with regulatory requirements (GDPR, HIPAA, SOX, etc.)
Conduct security assessments and vulnerability management
Cost Optimization & Performance: Monitor and optimize cloud resource costs through rightsizing and automation
Implement cost allocation and chargeback mechanisms
Performance tuning of data processing and analytics workloads
Capacity planning and resource forecasting
Collaboration & Support: Work closely with data engineers, data scientists, and analytics teams
Provide technical guidance and mentoring to junior team members
Participate in on-call rotation for platform support and incident response
Document processes, procedures, and system architecture
Essential Business Experience and Technical Skills
Required:
Bachelor's degree in Computer Science, Engineering, or related technical field, or 7+ equivalent professional experience will be considered
Cloud Platforms: 5+ years of experience with Microsoft Azure, including deep knowledge of Azure services (Azure SQL, Cosmos DB, Azure Data Factory, Synapse, Databricks, Data Lake, Machine Learning, etc.)
Infrastructure as Code: Proficiency in ARM templates, Bicep, Terraform, or similar tools
Containerization: Experience with Docker, Azure Container Instances, and Azure Kubernetes Service (AKS)
DevOps Skills
CI/CD: Strong experience with Azure DevOps, GitHub Actions, Jenkins, or similar platforms
Automation of infrastructure, application deployments using Azure DevOps Pipeline / Github actions.
Programming: Proficiency in Python, PowerShell, Bash, and/or other scripting languages
Monitoring & Logging: Experience with Azure Monitor, Log Analytics, Application Insights, or similar tools
Data Engineering: Knowledge of data pipeline orchestration tools (Databricks, Azure Data Factory)
Soft Skills
Excellent problem-solving and analytical skills
Strong communication and collaboration abilities
Ability to work in fast-paced, agile environments
Leadership and mentoring capabilities
Customer Service Orientation
Preferred:
Certifications
Microsoft Azure Solutions Architect Expert (AZ-305)
Microsoft Azure DevOps Engineer Expert (AZ-400)
Terraform Associate or Professional certification
Experience with multi-cloud environments (AWS, GCP)
MLOps
Experience with MLOps frameworks and tools (MLflow, Azure ML, Kubeflow
Understanding of machine learning lifecycle and model deployment strategies
GenAI exp. is preferred
Knowledge of data mesh and modern data architecture patterns
Data Technologies: Experience with SQL, NoSQL databases, data warehousing, and big data technologies
Security & Compliance: Strong understanding of cloud security principles and best practices
Experience with Azure Active Directory, RBAC, and identity management
Knowledge of data privacy regulations and compliance requirements
Experience with security scanning and vulnerability assessment tools
Experience with streaming data technologies (Apache Kafka, Azure Event Hubs)
Background in financial services, healthcare, or other regulated industries Experience with agile/scrum methodologies
At MetLife, we’re leading the global transformation of an industry we’ve long defined. United in purpose, diverse in perspective, we’re dedicated to making a difference in the lives of our customers. Equal Employment Opportunity/Disability/Veterans If you need an accommodation due to a disability, please email us at accommodations@metlife.com. This information will be held in confidence and used only to determine an appropriate accommodation for the application process. MetLife maintains a drug-free workplace.
#J-18808-Ljbffr