What are the responsibilities and job description for the Senior Solutions Architect position at AIT Global, Inc.?
Job Details
Job Title: Senior Solutions Architect
Location: Portland, OR
Location: Portland, OR
Job Summary:
Portland General Electric (PGE) is seeking a skilled Senior Solutions architect with expertise in designing and implementing cloud-based data solutions. The ideal candidate will have a strong background in cloud infrastructure, data warehousing, machine learning operations, and automation practices.
Key Responsibilities/Skills:
- Understand current business processes and capability requirements from architecture, integrations, and process standpoint.
- Perform market analysis and short list vendors for evaluation & lead demos with vendor, bringing along business.
- Build evaluation criteria to measure vendors and put together a capability, architecture, and cost analysis for the business.
- Design and implement cloud-based (AWS - preferred) data solutions, with an emphasis on performance optimization, scalability, and security.
- Implement cloud data governance, data security, and compliance regulations.
- Apply serverless automation frameworks, Dev/ML/Data Ops tools and CI/CD pipelines.
- Bring expertise in scripting and automation tools such as Python, Bash, Terraform, or CloudFormation for cloud-based integrations.
- Evaluate and select appropriate technologies and tools.
- Work closely with cross-functional teams, including business stakeholders, data engineers, DevOps, and cloud security teams, to ensure successful migration and deployment.
- Provide technical guidance to development team and application teams to migrate data from legacy systems (e.g., DataStage) to cloud-native solutions (e.g., AWS Glue, Redshift, Snowflake)
- Define and document architectural guidelines, standards, and best practices.
- Added advantage with ETL/ELT processes, particularly in transitioning from legacy tools like DataStage to cloud-native solutions.
- Deep understanding of various data modeling techniques (e.g., dimensional modeling, Data Vault, Data Mesh) and the ability to choose the appropriate model for different business needs. Experience with conceptual, logical, and physical data modeling.
- Experience with metadata management tools and processes, including data dictionaries, business glossaries, and data lineage tracking.
- Integrate AI/ML capabilities into business applications to drive innovation and automation.
- Hands-on experience with AWS services (e.g., EC2, S3, Lambda, SageMaker,etc..)
- Excellent communication, problem-solving and team collaboration skills.
- Ensure system performance, cost efficiency, and compliance with security best practices.
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