At a Glance
- Tasks: Build and manage data warehouses while driving analysis and process improvements.
- Company: Join Amazon's fast-growing Global Tax Data team.
- Benefits: Competitive salary, diverse culture, and opportunities for growth.
- Other info: Collaborate with tech partners and enhance your analytical skills.
- Why this job: Make a real impact on tax compliance with cutting-edge data analytics.
- Qualifications: Experience in data analysis, SQL, and data visualisation tools.
The predicted salary is between 49500 - 60500 £ per year.
Description
Global Tax Data (GTD) organization provides data management services and supports program and product initiatives that improve tax data integrity across Amazon's global indirect tax compliance operations.
GTD ensures timely, accurate data is available for tax compliance reporting and audit readiness, and our teams manage the tax data infrastructure, pipelines, reconciliation tools, and operational reporting that compliance teams rely on worldwide.
As a Business Intelligence Engineer (BIE) II in GTD, you'll build gold-standard analytics datasets and data mart/warehouses while driving the data analysis, reconciliation operations, root-cause investigations, and process improvements that directly support Amazon's monthly tax compliance cycles.
You'll partner cross-functionally with your customers in tax compliance and accounting, and with stakeholders across finance technology, to make sure the data behind every filing is complete, accurate, and delivered on time.
You'll also work closely with Data Engineering, Software Engineering, and Solutions Architects.
This is a hands-on role for someone who enjoys digging into large datasets — spotting patterns, explaining the story behind the variances, and driving issues to resolution independently.
You'll thrive here if you bring strong analytical skills, the ability (or a genuine eagerness to build it) to work with large-scale data, and the business judgment to translate tax and accounting context into the right system configurations.
- Key job responsibilities
- Build and own the Gold standard data mart/warehouse for business reporting and analysys
- Perform hands-on reconciliation and detailed analysis of large financial datasets each month, investigating and resolving discrepancies across source systems, tax reporting warehouses, and the general ledger.
- Troubleshoot data quality issues, identify root causes, and drive corrective actions with upstream and downstream teams.
- Partner with compliance and customer teams to understand reporting requirements and translate business objectives into clear data specifications and technical development requirements.
- Develop and maintain operational reports, dashboards, and metrics that give visibility into reconciliation health and data readiness.
- Identify opportunities to improve efficiency, controllership, and data quality — automating manual processes, reducing cycle time, and coaching customer teams on how to use the reporting and functionality you build.
- Own and manage SIM tickets and intake workflows, ensuring timely response and resolution for internal and external stakeholders.
- Support audit data requests by extracting, validating, and delivering data packages to auditors and tax authorities.
- Document standard operating procedures, runbooks, and process flows for recurring operational activities.
- Build strong relationships with key technology providers and technical teams across Amazon, and clearly explain financial and technical concepts to both technical and non-technical audiences.
- Contribute to Monthly and Quarterly Business Reviews (MBRs/QBRs) and operational readiness activities.
- About the team
We are a fast-growing team supporting the Corporate Tax function.
We seek candidates who are eager and able to learn new content quickly, who are willing to venture into unfamiliar territory, and who bring ironclad judgment and integrity when handling confidential information.
A day in the life
Work closely with Tech partners, non-tech customer and team to deliver the required solution.
- Basic Qualifications
- Experience in analyzing and interpreting data with Redshift, Oracle, No SQL etc.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with SQL
- Experience in the data/BI space
- Experience in tax, finance or a related analytical field
- Experience in Excel (including VBA, pivot tables, array functions, power pivots, etc.) and data visualization tools such as Tableau
- Experience defining requirements and using data and metrics to draw business insights
- Experience making business recommendations and influencing stakeholders
- Bachelor's degree in finance, accounting, business, economics, engineering , analytics, mathematics, statistics or a related technical or quantitative field
- Preferred Qualifications
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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.
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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
BIE II, Tax 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 BIE II, Tax in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Amazon Inc.!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like BIE II, Tax at Amazon Inc..
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Amazon Inc..
✨Apply Directly through Our Website
When you find a suitable opening like BIE II, Tax at Amazon Inc., make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace BIE II, Tax in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Amazon Inc., your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amazon Inc.. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Amazon Inc.
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Amazon Inc.!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
