| | Can you give a high-level overview of your team size, roles, its initiatives/deliverables, and any tool/technologies specific to your team/department/project they will be supporting: Team Size This role will be interacting different roles like BA, Sr Data Engineers, API Engineers, AWS Admins on the team.
This role will be supporting the Grant Management Technology Solutioning work, Technical Debt work as well to support the preparation of scope for the Data Stage Migration work which is on the roadmap for this year.
Tools/ Technology: Cloud platform (AWS, Snowflake), DevOps, ML , Data Ops
What would a day in the life of this role look like? Work with business partners on the grant management team to build capability matrix for evaluation for Grant Management Software Vendors. Further, will work with business partners to evaluate the current state and future state of Data Stage Jobs to help build a BSG package to present for funding.
Additionally, will lead the Technical Debt work to build framing for Dev Ops, ML Ops, Tagging, Reliability, Snowflake costs, etc in partnership with AWS Admins.
What interaction level with this role have the team members and hiring manager? Work closely with the teams on Snowflake and AWS cloud administration and support.
What would you say is the top priority for the worker over the first few weeks/months?: Grant Management Vendor Evaluation. Scaling framework for Tech Debt work
What do you foresee being the biggest challenge in this role? Getting up to speed quickly to deliver outcomes.
Is utilities experience required? Nice to have, not mandatory
Top 3 Must-Haves (Hard and/or Soft Skills):
1. AWS architecture along with AWS Services hands on knowledge
2. Architecture and Solution Assessment
3. Critical thinking and problem-solving skills
Top 3 Nice-To-Haves (Hard and/or Soft Skills)
1.Working experience of Cloud architectural patterns and frameworks
2. In-depth knowledge of AWS services, especially IAM, EC2, S3, RDS, and Sage Maker
3. DevOps/ML Ops Automation (Terraform, CloudFormation)
Certification Requirements (Any Preferences): AWS Certified Solutions Architect, Snowflake
How many years of experience are you looking for?: 5-7 year s experience
Job Title: Senior Solutions Architect
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. |
