Data & Analytics Solutions Architect (AWS + Snowflake + Cortex)
Job Description
Role - Technical Architect
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Location- Columbus, OH
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Experience - 6 - 14 Years
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Skill: Data & Analytics Solutions Architect (AWS + Snowflake + Cortex)
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Location: NJ/NYC, Columbus OH, Washington DC area, Milwaukee, Boston, Pittsburg PA, Troy MI
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Must Have Technical/Functional Skills:
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• 14+ years of experience in Enterprise Data Architecture, AWS Data Platforms, Snowflake, Data Engineering, and Cloud Modernization.
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• Proven experience in Enterprise Solution architecture using AWS, Snowflake, Cortex and related technology components across the Data to Insights end to end value chain.
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• Strong hands-on expertise in AWS Data Services, Snowflake, Snowflake Cortex, Snowflake Horizon Catalog, Apache Iceberg / Snowflake Open Catalog, Python, PySpark, and SQL.
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• Proven experience designing and implementing Lakehouse Architectures, enterprise data platforms, and modern analytics solutions on AWS.
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• Strong understanding of the Snowflake Data Cloud, including Snowflake SQL, Workflows, Snowpipe, Snowflake Model Registry, Snowflake Horizon Catalog, Serverless Compute, and Performance Optimization.
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• Experience building AI-enabled analytics solutions using Snowflake Cortex, semantic models, natural language analytics, and governed data access frameworks.
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• Expertise in Data Engineering including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps practices.
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• Strong knowledge of Enterprise Data Architecture, including data models, data products, lakehouse and warehouse patterns, semantic layers, and master/reference data management.
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• Experience implementing Security, Governance, and Compliance controls including IAM/RBAC, encryption, privacy, masking, auditability, retention, and responsible AI practices.
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• Proven experience leading architecture definition, HLD/LLD preparation, NFR assessment, migration planning, technical governance, and production readiness activities.
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• Experience supporting cloud transformation initiatives, solutioning, RFP responses, effort estimation, and client-facing architecture discussions.
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• Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.
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• Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.
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• Preferred certifications in AWS Solutions Architecture, Snowflake, Data Engineering, Enterprise Architecture, Security, or AI/ML.
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Roles & Responsibilities:
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• Engage with business and technology stakeholders to understand data, analytics, AI, and cloud transformation requirements.
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• Define end-to-end architecture for AWS Snowflake-based data, analytics, and AI platforms.
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• Design scalable, secure, and high-performance Lakehouse solutions using AWS Data Services, Snowflake, Apache Iceberg / Snowflake Open Catalog, and Snowfl ake Horizon Catalog.
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• Architect data ingestion, integration, batch, streaming, and data engineering solutions supporting enterprise analytics and AI use cases.
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• Design and implement AI-enabled analytics solutions using Snowflake Cortex, semantic models, and governed data access frameworks.
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• Establish data governance, security, metadata, lineage, observability, and responsible AI standards across the platform.
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• Lead data platform modernization, migration, and cloud transformation initiatives on AWS.
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• Define architecture standards, reusable frameworks, best practices, and DataOps delivery models.
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• Provide technical leadership across solution design, implementation, testing, migration, deployment, and production support activities.
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• Conduct architecture reviews, identify risks and dependencies, and guide teams on mitigation strategies and best practices.
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• Drive platform performance optimization, reliability improvements, and cost optimization across AWS and Snowflake environments.
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• Collaborate with data engineers, AI specialists, architects, platform teams, and client stakeholders to deliver enterprise-scale solutions.
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• Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops.
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• Mentor architects and engineers and contribute to capability development, technical assessments, and knowledge-sharing initiatives.
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• Develop reusable accelerators, reference architectures, implementation frameworks, and best practices for AWS Snowflake and AI solutions.
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