At a Glance
- Tasks: Guide customers through complex data transformation projects and build strong relationships with C-level executives.
- Company: Join Amazon's innovative Data & AI Practice and shape the future of cloud adoption.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on collaboration and innovation.
- Why this job: Make a real impact by solving complex business and technology challenges.
- Qualifications: Experience in cloud computing and IT implementation is essential.
The predicted salary is between 72000 - 88000 £ per year.
As a Data Consultant you will work with customers and partners, guiding them through planning, preparing and delivery of complex data transformation projects based on varying customer needs.
You will build and maintain strong stakeholder relationship with C-level executives to shape their cloud and data transformation roadmap.
On a daily basis, you will work together with customers to assess their organizational readiness to perform the cloud adoption.
You will guide them to define goals, objectives and business outcomes.
Together with the stakeholders, you will create and align a cloud vision to achieve those results.
You identify solutions that help a customer, partner, or an internal team overcome technical as well as organizational challenges.
You will collaborate with Subject Matter Experts to support pre-sales activities.
Do you have experience delivering IT solutions in agile environment - plan, organize, and manage all phases of a project lifecycle to ensure successful delivery?Come build the future with us.
Key job responsibilities Employ customer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, standard methodologies, project management and risk mitigation.*Work closely with AWS Engineering and Architecture teams to help ensure the success of project consulting engagements with customers.*Work directly with customers’ technical resources to devise and recommend solutions based on the understood requirements.*Think strategically about business, product, and technical challenges in an enterprise environment. *Analyse on-premises database environments such as Oracle, SQL Server, or other Commercial DB Engines to Open Source Engines like Aurora-Postgre SQL/My SQL or Red Shift, Dynamo DB.*Consult for optimal design of environments, analysing complex distributed production deployments, and making recommendations to optimize performance.*Develop innovative solutions to complex business and technology problems Be able to obtain and maintain a UK Government Security Clearance.
Further details found here: https://www. gov. uk/government/publications/united-kingdom-security-vetting-clearance-levels Basic qualifications- Experience and technical expertise (design and implementation) in cloud computing technologies- Experience in IT implementation Preferred qualification - Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies- Experience translating technical aspects of analysis and metrics into actionable insights for the advertiser and both technical and non-technical stakeholders Amazon is an equal opportunities employer.
We believe passionately that employing a diverse workforce is central to our success.
We make recruiting decisions based on your experience and skills.
We value your passion to discover, invent, simplify and build.
Protecting your privacy and the security of your data is a longstanding top priority for Amazon.
Please consult our Privacy Notice () to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information.
If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Data Consultant, Data & AI Practice employer: AmazonWebServices
At Amazon Web Services (AWS), we are committed to fostering a culture of innovation and inclusivity, making us an exceptional employer for those in the Site Reliability Engineering Services role. Our employees benefit from extensive mentorship and career growth opportunities, alongside a strong emphasis on work-life balance, ensuring that personal well-being is valued as much as professional success. Join us in building the future of cloud computing while being part of a team that celebrates diversity and encourages collaboration.
StudySmarter Expert Advice🤫
We think this is how you could land Data Consultant, Data & AI Practice
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like AmazonWebServices.
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We think you need these skills to ace Data Consultant, Data & AI Practice
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at AmazonWebServices, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at AmazonWebServices. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at AmazonWebServices
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at AmazonWebServices!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
