Position: Data & ML Architect | Solutions Architect | AWS certified
Category: Lead
English level: fluent
Years of experience: 5


I am certified AWS Solutions Architect with 5+ years of experience in building data and ML systems. I join projects for pre-sales, discovery, or advisory activities in most cases.

SOLUTIONS ARCHITECT
GlobalLogic - Jun 2023 - present 
Goal: serve as SME for data and ML solutions on AWS and assist with project initialization.
• Design and build scalable data and ML solutions in AWS.
• Help clients utilize GenAI capabilities to improve their business processes.
• Refactor applications to use serverless/event-driven architectures.
• Deliver GDPR-/PCI-/NIST-compliant data processing workloads.
• Manage and audit architecture documentation.
Toolset: AWS, Python, TOGAF/RUP

CLOUD CONSULTANT 
GlobalLogic - Jan 2022 - Jun 2023
Goal: take responsibility for implementation and design of data and ML solutions on AWS.
• Designed and built scalable data and ML solutions.
• Worked with stakeholders to gather (non-)functional requirements.
• Migrated existing data/ML workloads to the cloud with consequent refactoring. 
• Introduced MLOps practices to streamline and automate ML pipelines for clients.
 • Created architecture documentation and maintained track record of ADRs.
• Performed AWS Well-Architected review and recommend improvements.
Toolset: AWS, Python, Terraform, Docker, Databricks, MLflow.

SENIOR CLOUD ENGINEER 
GlobalLogic - Oct 2020 - Jan 2022
Goal: automate data science team workloads and implement DevOps best practicies.
• Assisted with designing and building data and ML platforms.
• Optimized data lake performance and related operational processes.
• Implemented best DevOps practices and established CI/CD pipelines.
• Created and maintained infrastructure using IaC tools (AWS CDK, Terraform).
• Completed initial AWS accounts bootstrapping.
• Performed AWS spendings planning and optimization.
Toolset: AWS, Python, Terraform/CDK, Docker, Jenkins.

DATA & ML ENGINEER
EPAM Systems - Nov 2018 - Oct 2020
Goal: prepare code ETL pipelines and train ML models for data-as-a-service product.
• Developed ETL pipelines to deliver data from a wide variety of data sources. 
• Trained ML models for time series forecasting and clustering.
• Built monitoring jobs and dashboards for ML inferences.
• Worked as on-site engineer for US-based client.
Toolset: AWS, Python, Spark, SQL, Databricks, Docker.

DATA ANALYST
Philip Morris Ukraine - Feb 2017 - Nov 2018
Goal: ensure data quality, perform data analysis and suggest improvements.