Job Description
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 years experience
Key Responsibilities/Skills:
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)
Added advantage with ETL/ELT processes, particularly in transitioning from legacy tools like DataStage to cloud-native solutions.
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..)
This role will be interacting different roles like BA, Sr Data Engineers, API Engineers, AWS Admins on the team.
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 mandatoryTop 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 years experience
Key Responsibilities/Skills:
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)
Added advantage with ETL/ELT processes, particularly in transitioning from legacy tools like DataStage to cloud-native solutions.
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..)
This role will be interacting different roles like BA, Sr Data Engineers, API Engineers, AWS Admins on the team.
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