At a Glance
- Tasks: Design and build scalable data pipelines for Prime Video's strategic decision making.
- Company: Join Amazon's innovative Prime Video team, expanding globally.
- Benefits: Competitive salary, diverse workplace, and opportunities for growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make a real impact on data-driven decisions in entertainment.
- Qualifications: Experience in programming, big data technologies, and data engineering.
The predicted salary is between 55000 - 70000 £ per year.
Amazon’s Prime Video is a premium on‑demand video entertainment service that offers customers an extensive selection of Amazon Original TV shows and movies, as well as exclusive content and live sports. Prime Video is rapidly expanding to over 240 countries and operates in a dynamic, innovative environment where customer focus drives everything we do.
The Prime Video Finance BI team seeks a Data Engineer to power the data infrastructure behind the service’s strategic and financial decision making. You will design and build scalable data pipelines and warehouse solutions that underpin business‑critical reporting used by leadership worldwide, collaborate with Finance and Business stakeholders to translate ambiguous business challenges into well‑engineered, automated data solutions, and directly enable the KPIs, metrics and analytics that drive Prime Video’s content and customer experience strategy.
Key job responsibilities
- Design, build, and maintain large‑scale data warehouse architectures and ETL/ELT pipelines that serve hundreds of users globally, ensuring high availability, performance, and data integrity.
- Apply cloud‑based AWS services (Redshift, Glue, EMR, S3, Lambda, Step Functions) to solve challenging problems around big data processing, data warehouse design, and self‑service data access.
- Develop automated data quality detection frameworks and monitoring systems to ensure data accuracy, completeness, and timeliness across critical datasets.
- Build and maintain infrastructure as code (CloudFormation, CDK, Terraform) to enable repeatable, version‑controlled deployment of data platform resources.
- Gather technical and business requirements from stakeholders in Finance and Business teams, and translate them into scalable, automated, and well‑engineered data solutions.
- Develop efficient systems and tools to process data at scale, using technologies that accommodate seasonal spikes and future growth.
- Drive automation and optimization across all areas of data‑warehouse/ETL maintenance, deployment, and operational excellence.
- Build strong partnerships with Business Intelligence, Core Analytics Tooling, and upstream data teams to enhance data sources, improve data models, and enable more scalable and accurate downstream reporting.
- Provide technical guidance on data modeling best practices, pipeline design patterns, and platform capabilities to support informed decision making across Prime Video.
BASIC QUALIFICATIONS
- Experience in at least one modern scripting or programming language such as Python, Java, Scala, or Node.js.
- Experience with big data technologies such as Hadoop, Hive, Spark, and EMR.
- Experience building/operating highly available, distributed systems for extraction, ingestion, and processing of large data sets.
- Experience with data modeling, warehousing, and building ETL pipelines.
- Knowledge of distributed systems as they pertain to data storage and computing.
- Knowledge of professional software engineering best practices for the full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence.
- Experience as a Data Engineer or in a similar role.
- Experience with SQL.
PREFERRED QUALIFICATIONS
- Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
- Experience working on and delivering end‑to‑end projects independently.
EEO & DIVERSITY
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. Amazon does not discriminate on the basis of protected veteran status, disability, or any other legally protected status.
WORKPLACE ACCOMMODATIONS
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 our accommodations page. If the country or region you are applying in isn’t listed on this page, contact your Recruiting Partner.
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.
Data Engineer, Prime Video Core Analytics and Tooling in London employer: ENGINEERINGUK
At Amazon's Prime Video, we pride ourselves on fostering a dynamic and innovative work culture that prioritises customer focus and employee growth. As a Data Engineer in our Finance BI team, you'll have the opportunity to work with cutting-edge technologies in a collaborative environment, driving impactful data solutions that shape the future of entertainment. With a commitment to diversity and inclusion, we offer a supportive workplace where your contributions are valued and your career can flourish.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, Prime Video Core Analytics and Tooling in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Amazon, especially in the Prime Video team. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your experience with AWS technologies and data engineering. This will not only impress interviewers but also give you something tangible to discuss during your interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data engineers, especially those related to ETL processes and big data technologies. Mock interviews with friends or using online platforms can help you nail it.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, you’ll be able to track your application status easily, so you won’t be left wondering what’s happening.
We think you need these skills to ace Data Engineer, Prime Video Core Analytics and Tooling in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Data Engineer role. Highlight your experience with AWS technologies and big data tools, as these are key to what we’re looking for at Prime Video.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that show how you’ve designed and built scalable data pipelines or tackled complex data challenges.
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and directly related to the job description.
Apply Through Our Website:We encourage you to apply through our website for the best chance of being noticed. It’s the easiest way for us to track your application and get back to you quickly!
How to prepare for a job interview at ENGINEERINGUK
✨Know Your Tech Stack
Familiarise yourself with the specific AWS technologies mentioned in the job description, like Redshift and Glue. Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the tech stack.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles. Think about specific instances where you designed scalable data pipelines or improved data quality, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Business Context
Research Prime Video's business model and how data engineering supports their strategic goals. Being able to articulate how your work as a Data Engineer can directly influence decision-making and customer experience will set you apart from other candidates.
✨Practice Coding and System Design
Brush up on your coding skills, especially in Python or Java, and be prepared for technical questions or live coding exercises. Additionally, think through system design scenarios related to data warehousing and ETL processes, as these are likely to come up during the interview.
