Why This Role Stands Out
This Enterprise Data Architect role offers a significant opportunity to shape innovative data platforms on AWS and Snowflake, driving AI-driven solutions within the manufacturing sector. If you excel at leading technical teams and communicating complex strategies to executives, this impactful position is an excellent next step in your career. Apply today to contribute to a leading company and expand your expertise.
Quick Overview
Seniority
Mid Senior
Work mode
On Site
Location
Peoria, IL, United States
Posted
22 hours ago
AWSEncryptionMLOpsMachine LearningNumPySnowflakeCloudFormationGitGitHub ActionsGitLab CILLMPandasPythonRESTTerraform
Job Description
Senior Solution Architect
Location:- Peoria, IL (Onsite from day 1)
This is day1 onsite in Peoria, IL
Key Capabilities
- 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
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