Senior Manager AWS Platforms & Data

Key Responsibilities

• Lead the design, implementation, and optimization of AWS-based cloud architectures
• Designing resilient, high-availability cloud architectures using Terraform or AWS CDK.
• Implementing AIOps strategies via Amazon DevOps Guru and AWS Compute Optimizer to automate root cause analysis and capacity planning.
• Orchestrating migrations of legacy workloads to EKS, ECS, or Lambda.
• Managing the AWS budget through rigorous tagging, savings plans, and spot instance utilization.
• Overseeing the Amazon Connect instance, including Salesforce integration and automated agent workflows
• Define and execute the organizations data strategy, including data governance, storage, and analytics
• Manage and mentor cross-functional teams of cloud engineers, data engineers, and analysts
• Executing MDM strategies and identity resolution frameworks to establish a unified "golden record."
• Governing an enterprise Data Catalog using AWS Glue to ensure data lineage and self-service accessibility.
• Integrating automated data quality checks (e.g., Great Expectations, Deequ) and maintaining event-driven architectures (SNS, SQS, Kinesis).
• Enforcing Data Vault principles to secure PHI/PII in compliance with HIPAA and GDPR.
• Drive data platform modernization, including data lakes, warehouses, and real-time pipelines
• Ensure best practices in security, compliance, and cost optimization across AWS environments
• Collaborate with business stakeholders to translate requirements into scalable data solutions
• Oversee DevOps and CI/CD pipelines for data and cloud infrastructure
• Stay ahead of emerging technologies and recommend innovations in cloud and data ecosystems

Required Qualifications

• Bachelors degree in Computer Science, Engineering, or related field
• 10+ years in Cloud Engineering, 3+ years in management or technical leadership role.
• Proven leadership experience managing technical teams and large-scale projects
• Deep expertise in AWS services (e.g., EC2, S3, Lambda, Redshift, Glue, EMR)
• Strong experience with data architectures (data lakes, warehouses, ETL/ELT pipelines)
• Proficiency in Python, SQL, and modern data tools
• Experience with infrastructure as code (e.g., Terraform, CloudFormation)
• Strong understanding of data governance, security, and compliance frameworks

Preferred Skills

• AWS Certifications (e.g., Solutions Architect, Data Analytics Specialty)
• Experience with big data frameworks (Spark, Had
  
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