AWS Solution Architect

As an AWS Managed Services Architect, you will play a pivotal role in architecting and optimizing the infrastructure and operations of a complex Data Lake environment for BOT clients. You'll leverage your strong expertise with AWS services to design, implement, and maintain scalable and secure data solutions while driving best practices. You will work collaboratively with delivery teams across the U.S., Costa Rica, Portugal, and other regions, ensuring a robust and seamless Data Lake architecture. In addition, you'll proactively engage with clients to support their evolving needs, oversee critical AWS infrastructure, and guide teams toward innovative and efficient solutions. This role demands a hands -on approach, including designing solutions, troubleshooting, optimizing performance, and maintaining operational excellence. Roles & Responsibilities: AWS Data Lake Architecture: Design, build, and support scalable, high -performance architectures for complex AWS Data Lake solutions. AWS Services Expertise: Deploy and manage cloud -native solutions using a wide range of AWS services, including but not limited to. Amazon EMR (Elastic MapReduce): Optimize and maintain EMR clusters for large -scale big data processing. AWS Batch: Design and implement efficient workflows for batch processing workloads. Amazon SageMaker: Enable data science teams with scalable infrastructure for model training and deployment. AWS Glue: Develop ETL/ELT pipelines using Glue to ensure efficient data ingestion and transformation. AWS Lambda: Build serverless functions to automate processes and handle event -driven workloads. AM Policies: Define and enforce fine -grained access controls to secure cloud resources and maintain governance. AWS IoT & Timestream: Design scalable solutions for collecting, storing, and analyzing time -series data. Amazon DynamoDB: Build and optimize high -performance NoSQL database solutions. Data Governance & Security: Implement best practices to ensure data privacy, compliance, and governance across the data architecture. Performance Optimization: Monitor, analyze, and tune AWS resources for performance efficiency and cost optimization. Develop and manage Infrastructure as Code (IaC) using AWS CloudFormation, Terraform, or equivalent tools to automate infrastructure deployment. Client Collaboration: Work closely with stakeholders to understand business objectives and ensure solutions align with client needs. Team Leadership & Mentorship: Provide technical guidance to delivery teams through design reviews, troubleshooting, and strategic planning. Continuous Innovation: Stay current with AWS service updates, industry trends, and emerging technologies to enhance solution delivery. Documentation & Knowledge Sharing: Create and maintain architecture diagrams, SOPs, and internal/external documentation to support ongoing operations and collaboration. Requirements Qualifications & Skills 7+ years of hands -on experience in cloud architecture and infrastructure (preferably AWS). 3+ years of experience specifically in architecting and managing Data Lake or big data solutions on AWS. Bachelor's Degree in Computer Science, Information Systems, or a related field (preferred). AWS Certifications such as Solutions Architect Professional or Big Data Specialty. Experience with Snowflake, Matillion, or Fivetran in hybrid cloud environments. Familiarity with Azure or GCP cloud platforms. Understanding of machine learning pipelines and workflows. Technical Skills: Expertise in AWS services such as EMR, Batch, SageMaker, Glue, Lambda, IAM, IoT TimeStream, DynamoDB, and more. Strong programming skills in Python for scripting and automation. Proficiency in SQL and performance tuning for data pipelines and queries. Experience with IaC tools like Terraform or CloudFormation. Knowledge of big data frameworks such as Apache Spark, Hadoop, or similar. Data Governance & Security: Proven ability to design and implement secure solutions, with strong knowledge of IAM policies and compliance standards. Problem -Solving: Analytical and problem -solving mindset to resolve complex technical challenges. Collaboration: Exceptional communication skills to engage with technical and non -technical stakeholders. Ability to lead cross -functional teams and provide mentorship.