Hello
ROLE: Data Architect with MLOps
Location- Reston, VA day one onsite and in person Interview.
As a Cloud and Data Architect, you will be responsible for leading architectural decisions for the Cloud and Data Enterprise Portfolios. You must have a deep understanding of technical architecture and hands on experience implementing solutions in cloud environments focused on AWS or Azure. You should have a strong understanding of industry best practices around enterprise cloud security, reference architectures, containerization, CI/CD, and cloud native design patterns.
Experience with microservices architectures, microservice orchestration, and MLOps platforms is a significant advantage. The architect must have experience implementing secure technical and deployment architectures using AWS services, Domino Data Labs, as well as engineering tools that support inter-service communication, data hydration, application security, platform resiliency, model lifecycle management, and enterprise operational governance.
Technical experience across multi-cloud environments (AWS, Azure, Google Cloud Platform) is a plus. Strong interpersonal and communication skills are required.
THE IMPACT YOU WILL MAKE
- This role offers you the flexibility to make each day your own while working alongside teams who care, so you can deliver on these responsibilities:
- Position yourself as a trusted advisor to business teams and partner with them to understand requirements for cloud implementations.
- Provide recommendations for cloud migration and develop technical implementation roadmaps for AWS adoption.
- Create application architecture, data architecture, deployment architectures, functional design specifications, and other technical deliverables.
- Design modern, scalable, secure, and resilient solutions on AWS that meet requirements for availability, performance, and compliance.
- Collaborate with Information Security, Compliance, Controls, and other teams to develop secure and compliant cloud solutions.
- Qualifications
Education & Experience
- Bachelor's degree in computer science or related field required, master's degree preferred.
- 12+ years of progressive hands on experience in application development, analysis, engineering, solution architecture, and technical leadership.
- Minimum 5 years of experience as a solution architect working with AWS or Azure.
- Experience with Architecture principles and the TOGAF framework is a plus.
- AWS Professional Certification preferred; AWS or Azure Architecture Associate Certification required.
- CISSP or equivalent security certification is a plus.
Technical Expertise
- Enterprise Data & Cloud Architecture
- Expertise managing Enterprise Data Platforms including Data Lakes, Data Warehouses, and Data Marts.
- Experience with real-time and near real-time data streaming platforms.
- Expertise with relational, semi-structured, and unstructured databases.
- Strong proficiency with Python or Java.
- Experience designing large-scale APIs, microservices, and distributed streaming-based solutions.
- Skilled in supporting and managing large, complex, and geographically distributed cloud environments.
- Strong background in risk assessment, control design, gap remediation, and impact analysis.
- MLOps Expertise
- Extensive experience with MLOps frameworks and enterprise ML lifecycle automation, including:
- ML Lifecycle Architecture & Automation
- Designing and implementing end to end MLOps pipelines: data ingestion, feature engineering, model training, tuning, evaluation, versioning, CI/CD for ML, approvals, and automated deployment.
- Establishing model governance, including lineage, auditability, explainability, data validation, and responsible AI controls.
- Model Deployment, Serving & Monitoring
- Designing microservice-based ML inference architectures using EKS/ECS, Lambda, Step Functions, and event-driven patterns.
- Implementing advanced model monitoring:
- drift detection
- data quality checks
- outlier detection
- performance degradation alerts
- CloudWatch / OpenTelemetry observability pipelines
- CI/CD for ML (MLOps)
- Building automated ML pipelines using CodePipeline, Bitbucket Pipelines, GitHub Actions, Jenkins, etc., integrated with container registries and SageMaker.
- Defining enterprise patterns for ML environment standardization, reproducibility, and secure deployment.
- Microservice Orchestration & Cloud-Native Engineering
- Experience with orchestrating microservices using AWS ECS, EKS, Fargate, Lambda, EventBridge, App Mesh, and Step Functions.
- Implementing service mesh patterns for service discovery, traffic routing, observability, and zero-trust communication.
- Designing event-driven architectures leveraging Kinesis, SNS/SQS, and Lambda.
- Experience building highly available, resilient, fault-tolerant cloud architectures.
- AWS & Cloud Infrastructure Expertise
- Proficiency with RDS PostgreSQL, Aurora, DynamoDB, and other AWS data services.
- Experience with AWS VPC design, IAM, CloudFormation, AMIs, multi-account strategy, and landing zone architecture.
- Strong knowledge of AWS services such as ELB, ElastiCache, CloudWatch, CloudTrail, S3, Lambda, Kinesis, App Mesh.
- Experience designing cloud logging, alerting, and observability frameworks.
- Expertise in AWS cloud security services and designing secure-by-default architectures.
- Experience with Jenkins, GitHub, Bitbucket, and Docker in DevOps workflows.
Sai Krishna Dasari || Sr US IT Recruiter
3535 Victory Group Way #4, Frisco, TX 75034
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