At a Glance
- Tasks: Design and optimise data architectures to transform raw data into reliable datasets.
- Company: Join Amazon, a leader in innovation and technology.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on continuous improvement.
- Why this job: Make a real impact by solving complex data challenges at scale.
- Qualifications: Experience in data engineering and building ETL pipelines.
The predicted salary is between 63000 - 77000 £ per year.
Are you passionate about building data solutions that power decisions at massive scale? As a Data Engineer II at Amazon, you will design, build, and optimize data architectures that turn raw information into reliable, high-quality datasets used by analysts, scientists, and engineering teams. You will work across the full data lifecycle — from ingesting and transforming semi-structured data streams to creating logical data models that drive physical design and enable self-service analytics. This role offers the opportunity to solve complex data challenges, improve how teams discover and trust their data, and directly influence business outcomes through the systems you create.
Key job responsibilities
- Design and implement ETL workflows and data pipelines that extract, transform, and load data at scale, ensuring stability, performance, and efficient resource usage across distributed systems and cloud infrastructure.
- Create and maintain logical and physical data models that accurately represent business requirements, enforce data integrity, and support downstream analytics and reporting needs.
- Write clean, well-documented code using SQL and scripting languages to automate data processes, optimize query performance, and build tools for tracking data lineage and improving data quality.
- Collaborate with analysts, scientists, and software engineers to understand data requirements, balance competing priorities, and deliver usable datasets that provide clear business value.
- Participate in code reviews, design discussions, and operational excellence initiatives, contributing to continuous improvement of team data solutions while mentoring peers on system architecture and best practices.
A day in the life
You will start your day reviewing pipeline health dashboards and resolving any data quality issues before they reach downstream consumers. From there, you might pair with a scientist to refine a data model, write and optimize SQL queries for a new reporting dataset, or evaluate a generative AI tool to accelerate a repetitive transformation task. Afternoons often include design reviews with your team, where you propose improvements to existing architectures or troubleshoot production incidents at their root cause.
About the team
Our team is focused on building reliable, scalable data infrastructure that empowers teams across Amazon to make faster, better-informed decisions. We value collaboration, technical curiosity, and a commitment to simplifying complex systems. As we continue to grow, you will have the opportunity to shape the tools and processes that define how data is managed and consumed. If you are excited about working in an inclusive environment where your ideas directly influence how we build for the future, we would love to hear from you.
Basic Qualifications
- Experience in data engineering
- Experience with data modeling, warehousing and building ETL pipelines
Preferred Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Data Engineer II (1 Year FTC), Supply Chain Optimization Technologies - Planning in London employer: Amazon Inc.
At Amazon Development Centre in Edinburgh, we are committed to fostering a collaborative and inclusive work culture that empowers our employees to innovate and excel. As an Applied Scientist in our Intelligent Talent Acquisition team, you will have the opportunity to work on cutting-edge machine learning technologies that directly impact recruitment processes, while benefiting from mentorship and professional growth opportunities. Join us to make a meaningful difference in how talent is acquired globally, all within a vibrant city known for its rich history and dynamic tech scene.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer II (1 Year FTC), Supply Chain Optimization Technologies - Planning in London
✨Tap into Online Data Science Communities
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We think you need these skills to ace Data Engineer II (1 Year FTC), Supply Chain Optimization Technologies - Planning in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Amazon Inc., make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Amazon Inc., emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Amazon Inc.’s attention and show the tangible impact of your work.
How to prepare for a job interview at Amazon Inc.
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Amazon Inc..
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Amazon Inc..
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Amazon Inc..
