▷ (Urgent Search) Sr. Delivery Consultant - Data Architect,ProServe SDT North

Amazon
London
11 months ago
Applications closed

Sr. Delivery Consultant - Data Architect, ProServe SDTNorth The Amazon Web Services Professional Services (ProServe) teamis seeking a skilled Delivery Consultant to join our team at AmazonWeb Services (AWS). In this role, you'll work closely withcustomers to design, implement, and manage AWS solutions that meettheir technical requirements and business objectives. You'll be akey player in driving customer success through their cloud journey,providing technical expertise and best practices throughout theproject lifecycle. Possessing a deep understanding of AWS productsand services, as a Delivery Consultant you will be proficient inarchitecting complex, scalable, and secure solutions tailored tomeet the specific needs of each customer. You’ll work closely withstakeholders to gather requirements, assess current infrastructure,and propose effective migration strategies to AWS. As a trustedadvisor to our customers, providing guidance on industry trends,emerging technologies, and innovative solutions, you will beresponsible for leading the implementation process, ensuringadherence to best practices, optimizing performance, and managingrisks throughout the project. The AWS Professional Servicesorganization is a global team of experts that help customersrealize their desired business outcomes when using the AWS Cloud.We work together with customer teams and the AWS Partner Network(APN) to execute enterprise cloud computing initiatives. Our teamprovides assistance through a collection of offerings which helpcustomers achieve specific outcomes related to enterprise cloudadoption. We also deliver focused guidance through our globalspecialty practices, which cover a variety of solutions,technologies, and industries. Key job responsibilities 1. Designingand implementing complex, scalable, and secure AWS solutionstailored to customer needs 2. Providing technical guidance andtroubleshooting support throughout project delivery 3.Collaborating with stakeholders to gather requirements and proposeeffective migration strategies 4. Acting as a trusted advisor tocustomers on industry trends and emerging technologies 5. Sharingknowledge within the organization through mentoring, training, andcreating reusable artifacts BASIC QUALIFICATIONS - 5+ years'experience architecting and implementing data platforms (Data Lake,Data Lakehouse, Data Mesh, Data Warehouse) at enterprise scale -Experience building end-to-end data solutions, including dataingestion (batch/streaming), storage, orchestration, governance,security, analytics, and observability. - Highly technical andanalytical mindset with ability to think strategically aboutbusiness, product, and technical challenges in an enterpriseenvironment - Extensive hands-on experience with data platformtechnologies, including at least three of: Spark, Hadoop ecosystem,orchestration frameworks, MPP databases, NoSQL, streamingtechnologies, data catalogs, BI and visualization tools -Proficiency in at least one programming language (e.g., Python,Java, Scala), infrastructure as code, cloud platforms, and SQL.PREFERRED QUALIFICATIONS - Experience in a lead Data Architect roleor similar Masters or PhD in Computer Science, Physics, Engineeringor Math. - Hands on experience leading large-scale global datawarehousing and analytics projects and ability to lead effectivelyacross organizations. - Understanding of database and analyticaltechnologies in the industry including MPP and NoSQL databases,Data Warehouse design, BI reporting and Dashboard development. -Customer facing skills to represent AWS well within the customer’senvironment and drive discussions with senior leaders regardingtrade-offs, best practices, project management and risk mitigation.Amazon is an equal opportunities employer. We believe passionatelythat employing a diverse workforce is central to our success. Wemake recruiting decisions based on your experience and skills. Wevalue your passion to discover, invent, simplify and build. Amazonis committed to a diverse and inclusive workplace. Amazon is anequal opportunity employer and does not discriminate on the basisof race, national origin, gender, gender identity, sexualorientation, protected veteran status, disability, age, or otherlegally protected status. #J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.