Solution Architect

Clevanoo LLC

United States

9 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Business Analytics Applications Cloud Computing Information Engineering Data Governance Data Masking Data Sharing Dataspaces Data Warehousing DevOps

+26 more

Github Identity and Access Management Python (Programming Language) NumPy Object-Oriented Software Development Role-Based Access Control Data Streaming Systems Integration Enterprise Data Management Scripting Large Language Models Snowflake Prompt Engineering Amazon Virtual Private Cloud (VPC) Git Cloudformation Pandas Pyspark Gitlab-ci Infrastructure Automation Frameworks Data Management Machine Learning Operations Functional Programming Cloudwatch Terraform Data Pipelines

Requirements

Experience with designing & delivering Enterprise data Platforms and awareness of all the areas of the data ecosystem (Data Management, Integrations (Streaming/Batch), Visualizations, Analytical Platforms etc.) Manufacturing domain experience Design Architectures: Build secure, scalable data solutions on AWS and Snowflake Lead Teams: Lead Onshore & Offshore teams to create the solution Drive Innovation: Apply AI awareness to increase productivity and develop AI solutions. Lead Readouts: Ability to present technical plans and business value to executive stakeholders clearly. Communication: Exceptional verbal and written communication skills for high-level leadership readouts.

Detailed Technical Skills Cloud Infrastructure (AWS): Deep expertise in IAM, VPC networking, CloudWatch, S3, IAM, Lambda, Glue, and EMR. Data Warehousing (Snowflake): Mastery of Snowpipe, streams, tasks, dynamic tables, data sharing, and storage optimization. Development & Scripting (Python): Advanced skills in PySpark, Pandas, NumPy, and building optimized, object-oriented data frameworks. DevOps & CI/CD: Hands-on experience with Git, GitHub Actions, GitLab CI, and Infrastructure as Code (Terraform or CloudFormation). AI & Machine Learning Awareness: Awareness of vector databases, LLM integration, prompt engineering, and MLOps pipelines (e.g., SageMaker). Data Governance & Security: Proven ability to implement role-based access control (RBAC), data masking, and encryption at rest/in transit.

Required Qualifications Experience: 15+ years of proven experience in data engineering, data warehousing, or enterprise architecture roles.