Data Architect
Indexed description
The position spans data platform engineering, self-service analytics enablement, and BI delivery through Quick Suite, all aligned with AWS cloud-native best practices.
Experience the freedom of remote work from anywhere in Georgia, whether from the comfort of your home, our modern offices in Tbilisi and Batumi or a coworking space in Kutaisi.
Responsibilities
- Configure, manage, and support Amazon SageMaker Unified Studio (SMUS), including data catalog, blueprints, and serverless compute capabilities
- Enable self-service data discovery, exploration, and analysis for business and technical users through SMUS
- Design and maintain SMUS blueprints and templates for repeatable, governed data workflows, while managing IAM domains, access policies, and governance configurations
- Architect and maintain the customer's data foundation on AWS, ensuring scalability, governance, and performance
- Design and optimize data lake architectures using Amazon S3, including modern storage formats (Parquet, Iceberg, Delta), and implement data cataloging, partitioning, and lifecycle management strategies for large-scale environments
- Integrate Amazon OpenSearch Service for search, analytics, and data exploration use cases
- Build and optimize serverless data pipelines using AWS Glue and AWS Lambda, including ETL/ELT jobs for data ingestion, transformation, and delivery
- Ensure pipeline reliability, monitoring, and error handling using AWS-native tooling such as CloudWatch, Glue job metrics, and S3 analytics
- Support the integration and delivery of Quick Suite (QuickSight / QuickSight Q) for analytics, dashboards, and self-service reporting
- Integrate agentic AI services to support intelligent data rendering, automated insights, and data-driven decision-making, collaborating with AI/ML teams to connect agentic workflows with the data foundation
- Apply AWS Well-Architected Framework principles with emphasis on security, reliability, performance efficiency, and cost optimization
- Document data architectures, SMUS configurations, pipeline designs, and operational runbooks, and conduct regular knowledge transfer sessions to build internal capability
- 7+ years of experience in data architecture and engineering roles, preferably within AWS cloud environments
- Expertise in Amazon SageMaker Unified Studio, including catalog, blueprints, and serverless compute
- Proficiency in AWS Glue, AWS Lambda, and serverless compute for data workflows
- Background in Data Lake architectures and Amazon S3 with modern storage formats (Parquet, Iceberg, Delta)
- Skills in Data Foundation Architecture, covering catalog, governance, and self-service enablement
- Familiarity with Amazon OpenSearch Service for search, analytics, and data exploration
- Proficient communication skills in English (B2 level or higher)
- Knowledge of Quick Suite / Amazon QuickSight
- Understanding of Agentic AI Services (e.g., Bedrock Agents, AgentCore)
- Competency in Amazon Lake Formation
- Skills in Infrastructure as Code (CDK, Terraform)
- Strong knowledge of Python
- We connect like-minded people
- Delivering innovative solutions to industry leaders, making a global impact
- Enjoyable working environment, whether it is the vibrant office or the comfort of your own home
- Opportunity to work abroad for up to two months per year
- Relocation opportunities within our offices in 55+ countries
- Corporate and social events
- We invest in your growth
- Leadership development, career advising, soft skills and well-being programs
- Certifications, including GCP, Azure and AWS
- Unlimited access to EPAM's internal learning database
- Free English classes with certified teachers
- We cover it all
- Participation in the Employee Stock Purchase Plan
- Monetary bonuses for engaging in the referral program
- Comprehensive medical & family care package
- Five trust days per year (sick leave without a medical certificate)
- Benefits package (sports activities, a variety of stores and services)
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