Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

AWS Architect - London,

DS Smith
London
10 months ago
Applications closed

Related Jobs

View all jobs

Lead AWS Data Engineer / Architect - Databricks - London

AWS Data Engineer - Permanent

Senior AWS Data Engineer - London - £125,000

Senior Data Engineer

Analytical Data Engineer

Senior Data Engineer | Cambridge | Greenfield Project

AWS Architect - London,

About the role

You will design and implement solutions using a range of AWS infrastructure, including S3, Redshift, Lambda, Step Functions, DynamoDB, AWS Glue, RDS, Athena, Kinesis. We also widely use other tech such as Databricks, Airflow, Power BI, etc, so experience in them is desirable. You will liaise with project teams to define requirements and refine solutions for our data projects. The ideal candidate will have exposure to CI/CD processes, or at least be keen to learn - our clients love infrastructure as code, and we like our engineers to own the deployment of their work. We need people who can work independently; but we're a close-knit, supportive team - we like to learn new things and share our ideas.

Key responsibilities

You will be responsible for leading the design and development of our data solution's architecture. Leading data pipeline architecture and identifying optimal data integration technologies to consolidate data from disparate systems. Leveraging cloud data platforms to democratize analytical capabilities. Working cross-functionally with stakeholders, and in particular our Bas, to translate business needs into technical data requirements and provide expertise on how to best leverage data to meet their goals.

Key Accountabilities:

  • Shaping & designing solutions (notably data analytics, data integration, data platform) leveraging AWS services including S3, Redshift, Lambda, Step Functions, DynamoDB, AWS Glue, RDS, Athena, and Kinesis for our Data Factory.

  • Driving the performance of assurance activity to delivery appropriate quality.

  • Collaborate with project teams to gather requirements, refine solutions, and scope data projects.

  • Gain exposure to and willingness to learn CI/CD processes to enable infrastructure as code and ownership of solution deployment.

  • Utilize additional technologies such as Databricks, Airflow, and Power BI to build robust data platforms and analytics capabilities.

  • Define data architecture strategy and standards across systems and projects.

  • Designing & developing data models aligned to the functional and non-functional requirements.

  • Ensure solutions meet scalability, flexibility, compliance, and other key data architecture principles.

  • Research and evaluate emerging technologies and methodologies to guide innovation on the organization's data strategy.

  • Lead the design and development of enterprise-wide data architecture and infrastructure

  • Define data standards, models, policies, flows, and integration processes to enable a scalable and unified Data Factory platform.

  • Manage data pipeline architecture leveraging tools like AWS Glue, Airflow, Databricks, etc.

  • Continuously monitor and optimize data infrastructure performance, costs, and reliability.

  • Establish comprehensive data governance practices, including security, privacy, and compliance controls.

  • Guide adoption of AI/ML capabilities by building trusted and well-governed data platforms.

About you

  • Strong experience in designing enterprise data architectures and solutions

  • Expertise with major cloud data platforms especially AWS

  • Hands-on experience building and optimizing big data pipelines, data lakes, warehouses with tools like Spark, Kafka, Airflow, dbt, etc.

  • Strong data modeling, database design, and SQL skills

  • Experience with BI/analytics platforms like Tableau, Looker, Power BI

  • Knowledge of data science disciplines like machine learning, AI, and statistical analysis

  • Understanding of data governance best practices related to security, compliance, privacy, and lifecycle management

  • Ability to communicate complex data concepts to business users and stakeholders

  • Natural curiosity to explore and learn new technologies like streaming data, graph databases etc.

  • Strategic thinker with ability to translate business needs into technology roadmaps and data capabilities

  • Passion for making data-driven decisions and enabling data democratization

  • Familiarity with agile software development methodologies

"To fulfil our purpose of redefining packaging for a changing world, we aim to build a diverse, motivated, and engaged workforce. Our goal is to create a culture of inclusion where everyone is treated fairly, differences are valued, and everyone has an equal opportunity to succeed.

Our people come from diverse backgrounds, bring different perspectives, ideas and experiences to generate unique solutions focused on present and future sustainability challenges. We welcome all candidates to apply, even those not meeting all criteria."

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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.