Data & Analytics Solutions Architect (AWS + Snowflake + Cortex)

Role - Technical Architect

Location- Columbus, OH

Experience - 6 - 14 Years

Skill: Data & Analytics Solutions Architect (AWS + Snowflake + Cortex)

The information below covers the role requirements, expected candidate experience, and accompanying qualifications.

Location: NJ/NYC, Columbus OH, Washington DC area, Milwaukee, Boston, Pittsburg PA, Troy MI

Must Have Technical/Functional Skills:

• 14+ years of experience in Enterprise Data Architecture, AWS Data Platforms, Snowflake, Data Engineering, and Cloud Modernization.

• Proven experience in Enterprise Solution architecture using AWS, Snowflake, Cortex and related technology components across the Data to Insights end to end value chain.

• Strong hands-on expertise in AWS Data Services, Snowflake, Snowflake Cortex, Snowflake Horizon Catalog, Apache Iceberg / Snowflake Open Catalog, Python, PySpark, and SQL.

• Proven experience designing and implementing Lakehouse Architectures, enterprise data platforms, and modern analytics solutions on AWS.

• Strong understanding of the Snowflake Data Cloud, including Snowflake SQL, Workflows, Snowpipe, Snowflake Model Registry, Snowflake Horizon Catalog, Serverless Compute, and Performance Optimization.

• Experience building AI-enabled analytics solutions using Snowflake Cortex, semantic models, natural language analytics, and governed data access frameworks.

• Expertise in Data Engineering including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps practices.

• Strong knowledge of Enterprise Data Architecture, including data models, data products, lakehouse and warehouse patterns, semantic layers, and master/reference data management.

• Experience implementing Security, Governance, and Compliance controls including IAM/RBAC, encryption, privacy, masking, auditability, retention, and responsible AI practices.

• Proven experience leading architecture definition, HLD/LLD preparation, NFR assessment, migration planning, technical governance, and production readiness activities.

• Experience supporting cloud transformation initiatives, solutioning, RFP responses, effort estimation, and client-facing architecture discussions.

• Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.

• Preferred certifications in AWS Solutions Architecture, Snowflake, Data Engineering, Enterprise Architecture, Security, or AI/ML.

Roles & Responsibilities:

• Engage with business and technology stakeholders to understand data, analytics, AI, and cloud transformation requirements.

• Define end-to-end architecture for AWS Snowflake-based data, analytics, and AI platforms.

• Design scalable, secure, and high-performance Lakehouse solutions using AWS Data Services, Snowflake, Apache Iceberg / Snowflake Open Catalog, and Snowfl ake Horizon Catalog.

• Architect data ingestion, integration, batch, streaming, and data engineering solutions supporting enterprise analytics and AI use cases.

• Design and implement AI-enabled analytics solutions using Snowflake Cortex, semantic models, and governed data access frameworks.

• Establish data governance, security, metadata, lineage, observability, and responsible AI standards across the platform.

• Lead data platform modernization, migration, and cloud transformation initiatives on AWS.

• Define architecture standards, reusable frameworks, best practices, and DataOps delivery models.

• Provide technical leadership across solution design, implementation, testing, migration, deployment, and production support activities.

• Conduct architecture reviews, identify risks and dependencies, and guide teams on mitigation strategies and best practices.

• Drive platform performance optimization, reliability improvements, and cost optimization across AWS and Snowflake environments.

• Collaborate with data engineers, AI specialists, architects, platform teams, and client stakeholders to deliver enterprise-scale solutions.

• Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops.

• Mentor architects and engineers and contribute to capability development, technical assessments, and knowledge-sharing initiatives. xhqgsiq

• Develop reusable accelerators, reference architectures, implementation frameworks, and best practices for AWS Snowflake and AI solutions.