At a Glance
- Tasks: Build tools and data pipelines while creating impactful reports and visualisations.
- Company: Join Amazon, one of the most visited sites on the Internet.
- Benefits: Competitive pay, hybrid working, networking opportunities, and mentorship.
- Other info: Potential for a graduate role after internship completion.
- Why this job: Make a real impact in a fast-paced environment with exciting projects.
- Qualifications: Currently studying computer engineering or a related field with SQL experience.
The predicted salary is between 63000 - 77000 £ per year.
Do you love building tools and data pipelines? Are you excited by the opportunity to create clear effective reports and data visualizations, and collaborate with stakeholders to answer key business questions? Do you want to be a part of a fast-paced environment and contribute to one of the most visited sites on the Internet? If this describes you, consider joining us as an intern. Amazon is looking for a data engineer intern to join one our many lines of business.
Responsibilities:
- Design, implement, and automate deployment of our distributed system for collecting and processing log events from multiple sources.
- Design data schema and operate internal data warehouses and SQL/NoSQL database systems.
- Own the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards to drive key business decisions.
- Monitor and troubleshoot operational or data issues in the data pipelines.
- Drive architectural plans and implementation for future data storage, reporting, and analytic solutions.
- Work collaboratively with Business Analysts, Data Scientists, and other internal partners to identify opportunities/problems.
- Provide assistance to the team with troubleshooting, researching the root cause, and thoroughly resolving defects in the event of a problem.
Requirements:
- Currently enrolled in a Bachelor’s or Master´s degree program in computer engineering, computer science, or a similar technical field.
- Advanced knowledge and/or experience using SQL.
- Experience with data querying or modeling with SQL, Excel.
- Experience with scripting language (e.g., Python, Java, or R).
- Knowledge of BI analytics/reporting/visualization tools (e.g., Tableau, AWS QuickSight, COGNOS, or other third-party tools).
Preferred:
- Master’s or advance technical degree.
- Proficient in at least one or more query language, schema definition language, and scripting language.
- Knowledge of writing and optimizing SQL queries in a business environment with large-scale, complex datasets.
- Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project.
- Experience with big data processing technology (e.g., Hadoop or ApacheSpark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments.
- Ability to deal with ambiguity in a fast-paced environment.
Conditions:
- Competitive pay.
- Impactful project and internship/role deliverables.
- Hybrid working (team dependent).
- Networking opportunities with fellow interns.
- Internships events such as speaker series, intern panels, Leadership Principles sessions, Amazon writing skills sessions.
- Mentorship and career development.
- If you’re successful during your internship, you could be considered for a graduate role after finishing your university studies.
- Internship start dates vary throughout the year. Internship ideal length is 6 months.
Data engineer in distributed systems 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 in distributed systems in London
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Data engineer in distributed systems in London
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Amazon Inc. will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Amazon Inc.
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Amazon Inc..
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Amazon Inc. that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
