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- Tasks: Design and implement scalable data solutions using AWS for Amazon's finance platform.
- Company: Join Amazon's Finance Tech team, shaping the future of finance data globally.
- Benefits: Enjoy a dynamic work environment with opportunities for innovation and growth.
- Why this job: Be part of a team that influences key business decisions and drives impactful change.
- Qualifications: 3+ years in data engineering, experience with SQL and data modelling required.
- Other info: Inclusive culture with support for diverse needs during the hiring process.
The predicted salary is between 43200 - 72000 £ per year.
Does the prospect of dealing with massive volumes of data excite you? Do you want to lead scalable data engineering solutions using AWS technologies? Do you want to create the next-generation tools for intuitive data access? Amazon\’s Finance Tech team needs a Data Engineer to shape the future of the Amazon finance data platform by working with stakeholders in North America, Asia and Europe. The team is committed to building the next generation big data platform that will be one of the world\’s largest finance data warehouses by volume to support Amazon\’s rapidly growing and dynamic businesses, and use it to deliver the BI applications which will have an immediate influence on day-to-day decision making. Members of the team will be challenged to innovate using the latest big data techniques. We are looking for a passionate data engineer to develop a robust, scalable data model and optimize the consumption of data sources required to ensure accurate and timely reporting for the Amazon businesses. You will share in the ownership of the technical vision and direction for advanced reporting and insight products. You will work with top-notch technical professionals developing complex systems at scale and with a focus on sustained operational excellence. We are looking for people who are motivated by thinking big, moving fast, and exploring business insights. If you love to implement solutions to hard problems while working hard, having fun, and making history, this may be the opportunity for you.
Key job responsibilities
Design, implement, and support a platform providing secured access to large datasets. Interface with tax, finance and accounting customers, gathering requirements and delivering complete BI solutions. Collaborate with Finance Analysts to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation. Model data and metadata to support ad-hoc and pre-built reporting. Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions. Tune application and query performance using profiling tools and SQL. Analyze and solve problems at their root, stepping back to understand the broader context. Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets. Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.
BASIC QUALIFICATIONS
– 3+ years of data engineering experience
– Experience with data modeling, warehousing and building ETL pipelines
– Experience with SQL
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)
Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Data Engineer-II, Fintech employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer-II, Fintech
✨Tip Number 1
Familiarise yourself with AWS technologies, especially those mentioned in the job description like Redshift and S3. Having hands-on experience or even completing relevant online courses can give you a significant edge during discussions.
✨Tip Number 2
Network with current or former employees of Amazon's Finance Tech team. Engaging with them on platforms like LinkedIn can provide insights into the team culture and expectations, which can be invaluable during your interview.
✨Tip Number 3
Prepare to discuss specific examples of your past projects involving data modelling and ETL pipelines. Be ready to explain the challenges you faced and how you overcame them, as this will demonstrate your problem-solving skills.
✨Tip Number 4
Stay updated on the latest trends in big data technologies. Being able to discuss recent advancements or tools you've experimented with can show your passion for the field and your commitment to continuous learning.
We think you need these skills to ace Data Engineer-II, Fintech
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with AWS technologies and SQL. Use keywords from the job description to demonstrate that you meet the qualifications.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your skills align with the role. Mention specific projects or experiences that showcase your ability to handle large datasets and work with stakeholders.
Showcase Technical Skills: Include a section in your application that lists your technical skills, especially those related to data modelling, ETL pipelines, and any AWS services you've worked with. This will help the hiring team quickly see your qualifications.
Prepare for Technical Questions: Anticipate technical questions related to data engineering and AWS technologies. Be ready to discuss your problem-solving approach and provide examples of how you've tackled challenges in previous roles.
How to prepare for a job interview at Amazon
✨Showcase Your Data Engineering Experience
Be prepared to discuss your previous data engineering projects in detail. Highlight your experience with data modelling, ETL pipelines, and any specific challenges you faced and overcame. This will demonstrate your hands-on expertise and problem-solving skills.
✨Familiarise Yourself with AWS Technologies
Since the role involves using AWS technologies, make sure you understand key services like Redshift, S3, and AWS Glue. Be ready to explain how you've used these tools in past projects or how you would approach using them in this role.
✨Prepare for Technical Questions
Expect technical questions related to SQL and data warehousing. Brush up on your SQL skills and be ready to solve problems on the spot. Practising common data engineering scenarios can help you feel more confident during the interview.
✨Demonstrate Your Collaborative Skills
The job requires working closely with finance analysts and other stakeholders. Be ready to share examples of how you've successfully collaborated in the past, focusing on communication and teamwork to achieve common goals.
