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 automation and optimization.
- 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 60000 - 80000 £ 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.
- 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.
- 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.
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 employer: ENGINEERINGUK
Amazon's Prime Video offers a vibrant and innovative work environment where Data Engineers play a crucial role in shaping the future of entertainment through data-driven insights. Employees benefit from a culture that prioritises diversity, collaboration, and continuous learning, with ample opportunities for professional growth and development. Located in a dynamic tech hub, team members enjoy access to cutting-edge technologies and the chance to work on impactful projects that reach millions of customers worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer, Prime Video Core Analytics and Tooling
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Prime Video on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can talk confidently about data pipelines, AWS services, and any big data tech you've worked with. Practice coding challenges to keep your skills sharp!
✨Tip Number 3
Showcase your projects! If you've built any cool data solutions or automated processes, be ready to discuss them in detail. Real-world examples can set you apart from other candidates.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining the team at Prime Video.
We think you need these skills to ace Data Engineer, Prime Video Core Analytics and Tooling
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, AWS technologies, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to Prime Video's success. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills:Don’t forget to showcase your technical skills in your application. Mention your experience with programming languages like Python or Java, and any big data technologies you’ve used. We love seeing candidates who are hands-on with the tools we use!
Apply Through Our Website:We encourage you to apply through our website for the best chance of being noticed. It’s super easy, and you’ll be able to track your application status. Plus, it shows us you’re serious about joining the team!
How to prepare for a job interview at ENGINEERINGUK
✨Know Your Tech Stack
Familiarise yourself with the specific AWS services mentioned in the job description, like Redshift and Glue. Be ready to discuss how you've used these technologies in past projects, as this will show your practical experience and understanding of the tools they'll expect you to use.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles. Think about times when you translated ambiguous business requirements into clear, automated data solutions. This will demonstrate your ability to think critically and work collaboratively with stakeholders.
✨Brush Up on Data Modelling
Since data modelling is a key part of the role, make sure you can explain your approach to designing data warehouses and ETL pipelines. Be ready to discuss best practices and any frameworks you've developed for ensuring data quality and integrity.
✨Practice Your Coding Skills
As coding is essential for this position, practice writing scripts in Python or Java. You might be asked to solve a coding problem during the interview, so being comfortable with coding challenges will help you stand out as a candidate.
