
Sr. Specialist Analytics Solutions Architect, Amazon Web Services, Wwps Slg-Edu Data And AI Specialists
Job Description
Summary
Lead public sector customers in designing and implementing advanced AWS analytics, AI/ML, and data solutions as a Senior Specialist Solutions Architect.
## Senior Analytics Specialist Solutions Architect, Public Sector
- *About the Role:**
- *Key Responsibilities:**
- Lead technical engagements for data lakes, data warehousing, real-time analytics, and AI/ML use cases.
- Deliver proofs-of-concept and workshops demonstrating AWS analytics and GenAI services.
- Collaborate with customer leadership and technical teams to design scalable, secure, and cost-effective data architectures.
- Influence AWS service team roadmaps by advocating for customer needs.
- Create reusable technical content, including reference architectures, whitepapers, and enablement materials.
- Mentor and drive enablement for AWS field solution architects.
- Travel up to 30% for customer and partner engagements.
- *Basic Qualifications:**
- 8+ years experience in data & analytics, software development, or cloud infrastructure.
- 3+ years experience designing and implementing analytics or data platforms.
- Deep expertise in cloud data services (e.g., data lakes, data warehouses, big data, search, streaming).
- Experience architecting and migrating large-scale data solutions to the cloud.
- *Preferred Qualifications:**
- 5+ years in infrastructure architecture, database architecture, or networking.
- Familiarity with Generative AI, AI/ML tools, and their integration into data platforms.
- Hands-on experience with AWS analytics services (e.g., Redshift, Glue, Athena, Kinesis, QuickSight).
- AWS certification(s) in Data Analytics, Machine Learning, or Solutions Architecture.
- Demonstrated ability to lead technical customer engagements and build lasting relationships.
- *Compensation:**
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Company Details
About
Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered, pay-as-you-go basis. Clients will often use this in combination with autoscaling. These cloud computing web services provide various services related to networking, compute, storage, middleware, IoT and other processing capacity, as well as software tools via AWS server farms. This frees clients from managing, scaling, and patching hardware and operating systems. One of the foundational services is Amazon Elastic Compute Cloud (EC2), which allows users to have at their disposal a virtual cluster of computers, with extremely high availability, which can be interacted with over the internet via REST APIs, a CLI or the AWS console. AWS's virtual computers emulate most of the attributes of a real computer, including hardware central processing units (CPUs) and graphics processing units (GPUs) for processing; local/RAM memory; hard-disk (HDD)/SSD storage; a choice of operating systems; networking; and pre-loaded application software such as web servers, databases, and customer relationship management (CRM).