Sr. Analytics & AI Specialist Solutions Architect, ASPI, AutoMfg

Are you a customer-obsessed leader with deep expertise in Data, Analytics, and Artificial Intelligence? Do you have the strategic vision and business acumen to shape multi-year AI transformation programs for the world's largest enterprises? Do you thrive at the intersection of novel technology and complex business challenges? Join AWS Specialists & Partners for Industries (ASPI) organization within the Data & AI Specialists team for Automotive & Manufacturing as a Principal Solutions Architect, requiring exceptional non-formal leadership, cross-functional orchestration, and strategic impact at the most senior customer and AWS leadership levels.

The ASPI organization is responsible for driving revenue and accelerating adoption of cloud and partner services across our most strategic global customers. We work backwards from our customers’ most complex and business-critical challenges to develop and execute go-to-market plans that transform ideas into scalable, high-impact businesses. ASPI teams include business development specialists and specialized solution architects. As part of ASPI, you will contribute across the full lifecycle of AWS customer initiatives – from shaping new service and solution concepts to accelerating adoption of established offerings.

We pride ourselves on thinking big, delivering exceptional customer outcomes, and collaborating seamlessly across AWS as #One Team.

In this role you will be the senior technical authority helping our largest customers design and adopt modern data and analytics platforms on AWS.

Analytics Architecture Design:
Provide deep technical expertise across the AWS analytics portfolio — including Amazon Redshift, Amazon Athena, Amazon EMR, AWS Glue, Amazon Kinesis, Amazon Open Search, Amazon Quick Sight, and the broader data ecosystem — to guide complex customer engagements from vision through implementation.

Data Platform Strategy:
Partner with customers to design and implement modern data platform architectures — centralized data lakes, data mesh patterns, data products, metadata management, and data governance frameworks — that enable trusted, self-service analytics across the enterprise.

Agentic AI Enablement:
Design the data foundation that makes enterprise data agent-ready — building the context, semantic, and ontology layers (knowledge graphs, business metadata, semantic models, governed catalogs) that give AI agents accurate, trusted business context. Bridge data engineering and AI teams so agentic and analytical workloads can reason over the same governed data estate at scale.

Solution Design & Deployment:
Design and deploy scalable, high-performance data warehousing, data lake, and real-time analytics solutions tailored to each customer s business requirements.

Field Enablement:
Create reusable enablement materials and reference architectures that help the broader SA population integrate AWS analytics solutions into customer architectures.

Cross-Functional Collaboration:

Partner with account teams, specialist sellers, Professional Services, and partners to drive analytics adoption and deliver comprehensive, end-to-end data solutions.

Thought Leadership & Influence:
Act as a trusted advisor to customer executives and technical leaders, represent AWS analytics at industry and field events, and channel field insights back to service teams to shape the analytics roadmap.

Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

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