Solutions Architect - Amazon QuickSight

Amazon
London
1 month ago
Applications closed

Related Jobs

View all jobs

Resident Solutions Architect - Databricks

AI Solutions Architect (R122902 AI Solutions Architect)

Resident Solutions Architect

Development & Cloud Solutions Architect

Data & AI Solutions Architect

Pre-sales Solutions Architect (Digital Native/Start-up) London, United Kingdom

Job ID: 2826021 | Amazon Web Services Australia Pty Ltd

Within the Gen AI/ML Specialist organization, this position is part of the Worldwide Specialist Solution Architecture Team, where you will join a global team for Amazon QuickSight (inclusive of Amazon Q). You will help guide customers in their adoption of Q and QuickSight through the creation of scalable enablement mechanisms, deep dive technical guides, and 1:1 engagement with customers as they evaluate service capabilities. You partner with technical and field teams across AWS and bring the voice of the customer into our product development roadmap.


Key job responsibilities

  1. Design and develop solutions and prototypes for customers that make the best use of Amazon QuickSight, including Generative BI capabilities of Amazon Q in QuickSight, and educate customers on how to integrate dashboards and Q&A experiences into their custom applications.
  2. Collaborate with AWS field sales, training, and support teams to ensure customer success.
  3. Create reusable customer content, such as demos, presentations, documentation, blogs, etc., that will drive adoption of Amazon QuickSight.
  4. Act as technical liaison between customers and the service engineering teams, providing product improvement feedback to AWS developers and accelerating the adoption of new features in customer deployments.
  5. Share what you know by capturing best-practice knowledge from engineering and field teams, including reference architectures and patterns amongst the worldwide AWS solution architect community in order to build a strong worldwide database, analytics and AI/ML community.
  6. Evangelize AWS services and solutions that benefit customers and publicly speak at events such as AWS Summits and AWS re:Invent.


A day in the life

Your daily schedule will be a mix of solving customers' challenges and creating scalable assets to further promote the knowledge and understanding of Amazon QuickSight and Amazon Q in QuickSight. You will collaborate with field teams to drive successful customer outcomes, as well as collaborate with service teams to incorporate customers' feedback into the roadmap. You will work closely with Go-To-Market (GTM) Specialist counterparts to develop a strategy to drive customer adoption further in your territory through 1:1 customer engagement and 1:many virtual and in-person events.


BASIC QUALIFICATIONS

  1. 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience.
  2. 3+ years of design, implementation, or consulting in applications and infrastructures experience.
  3. Bachelor's degree.
  4. 2+ years of experience developing dashboards with a Business Intelligence platform such as QuickSight, Tableau, PowerBI, Looker, Thoughtspot, Microstrategy, Sisense, Domo, etc.


PREFERRED QUALIFICATIONS

  1. Experience in technology/software sales, pre-sales, or consulting.
  2. Experience with scripting (e.g. Python, PowerShell).
  3. Experience with AWS technologies.
  4. 2+ years experience architecting and implementing Business Intelligence solutions into production.


Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.


IDE statement:
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer, and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected attributes.


Posted:November 19, 2024 (Updated 10 days ago)

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.