Solution Architect – Data Engineering (Snowflake & AWS)
DXC Technology (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 22–36 LPA
Posted on 31 Aug
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at DXC Technology
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at DXC Technology you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design and implementation of scalable, secure data platforms and analytics solutions using Snowflake and AWS technologies.
- Define architecture standards, governance frameworks, and conduct reviews to ensure technical quality and compliance across enterprise transformation projects.
- Provide technical leadership, mentor engineering teams, and support solution estimation and client presentations.
Minimum Requirements
- Strong expertise in Snowflake and AWS cloud services relevant to data engineering (e.g., S3, Glue, Redshift, EMR, Lake Formation, Lambda, IAM, Kinesis).
- Experience designing modern data architectures including Data Lakes, Lakehouses, Data Warehouses, Data Mesh, or Data Fabric.
- Proven ability to lead technical teams and conduct architecture governance across complex projects.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in architecting cloud-native data solutions that prioritize scalability, security, and cost optimization at enterprise scale.
- Skilled in translating complex business requirements into technical architectures and influencing cross-functional teams.
- Background in leading migration and modernization initiatives of legacy data platforms to cloud environments.