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Enterprise Data & Cloud Architecture
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Expertise managing Enterprise Data Platforms including Data Lakes, Data Warehouses, and Data Marts.
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Experience with real-time and near real-time data streaming platforms.
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Expertise with relational, semi-structured, and unstructured databases.
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Strong proficiency with Python or Java.
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Experience designing large-scale APIs, microservices, and distributed streaming-based solutions.
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Skilled in supporting and managing large, complex, and geographically distributed cloud environments.
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Strong background in risk assessment, control design, gap remediation, and impact analysis.
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MLOps Expertise
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Extensive experience with MLOps frameworks and enterprise ML lifecycle automation, including:
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ML Lifecycle Architecture & Automation
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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.
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Establishing model governance, including lineage, auditability, explainability, data validation, and responsible AI controls.
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Model Deployment, Serving & Monitoring
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Designing microservice-based ML inference architectures using EKS/ECS, Lambda, Step Functions, and event-driven patterns.
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Implementing advanced model monitoring:
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drift detection
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data quality checks
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outlier detection
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performance degradation alerts
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CloudWatch / OpenTelemetry observability pipelines
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CI/CD for ML (MLOps)
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Building automated ML pipelines using CodePipeline, Bitbucket Pipelines, GitHub Actions, Jenkins, etc., integrated with container registries and SageMaker.
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Defining enterprise patterns for ML environment standardization, reproducibility, and secure deployment.
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Microservice Orchestration & Cloud-Native Engineering
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Experience with orchestrating microservices using AWS ECS, EKS, Fargate, Lambda, EventBridge, App Mesh, and Step Functions.
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Implementing service mesh patterns for service discovery, traffic routing, observability, and zero-trust communication.
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Designing event-driven architectures leveraging Kinesis, SNS/SQS, and Lambda.
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Experience building highly available, resilient, fault-tolerant cloud architectures.
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AWS & Cloud Infrastructure Expertise
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Proficiency with RDS PostgreSQL, Aurora, DynamoDB, and other AWS data services.
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Experience with AWS VPC design, IAM, CloudFormation, AMIs, multi-account strategy, and landing zone architecture.
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Strong knowledge of AWS services such as ELB, ElastiCache, CloudWatch, CloudTrail, S3, Lambda, Kinesis, App Mesh.
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Experience designing cloud logging, alerting, and observability frameworks.
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Expertise in AWS cloud security services and designing secure-by-default architectures.
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Experience with Jenkins, GitHub, Bitbucket, and Docker in DevOps workflows.