AWS Data Architect
4 days ago
Role: Solutions Architect - AWS Data and Analytics GTM
Experience: 8+ Years, Minimum 5 years on AWS
Work location: Mumbai/Bangalore/ Trivandrum (Hybrid)
Responsibilities
- Be a trusted technical advisor to customers and solutions for complex Cloud & Data related technical challenges.
- Be a thought leader in architecture design and development of cloud data analytics solutions.
- Liaison with internal and external stakeholders to design optimized data analytics solutions on AWS cloud
- Partner with SMEs and Solutions Architects from leading cloud providers to present solutions to customers
- Support Quantiphi Sales and GTM teams from a technical perspective in building proposals and SOWs
- Lead discovery and design workshops with potential customers across the globe
- Design and deliver thought leadership webinars and tech talks alongside customers and partners.
- Identify areas for productization and feature enhancement for Quantiphi's product assets.
Technical Qualifications
- Experience in designing, deploying, and operating highly available, scalable, secure, and fault-tolerant systems using Amazon Web Services (AWS) products like DMS, SCT Redshift, Lambda, Glue, S3, EMR, Kinesis
- Strong experience in Data Migration using DMS and SCT services of AWS
- Strong Experience in migration and modernization of databases and data warehouses on AWS cloud.
- Good understanding of traditional databases and data warehouses like Oracle, Teradata, and Netezza.
- Experience in developing ETL solutions using SSIS/Talend/Informatica
- Experience with Back-end engineering /API development using Python etc.
- Strong knowledge in OLTP/OLAP Systems, Dimensional Strategies - Star Schema, Snowflake Schema, and Ralph Kimball Methodology
- Ability to integrate 3rd party API programmatically. Ability to access AWS programmatically via its API
• Big data/Stream platform development experience Kafka - Write SQL code - Queries/Stored Procedures/Functions.
- Previous experience in working with distributed architectures like Hadoop, Map-reduce, etc.
- Understanding of DevOps best practices with CICD, Infrastructure as Code, etc.
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