Data Engineer, FinOps FP&A, FinOps FP&A
Data Engineer, FinOps FP&A, FinOps FP&A

Data Engineer, FinOps FP&A, FinOps FP&A

London Full-Time 36000 - 60000 Β£ / year (est.) No home office possible
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At a Glance

  • Tasks: Join us to design and implement data solutions that process billions of records daily.
  • Company: Be part of Amazon Finance Technology, shaping the future of finance data platforms.
  • Benefits: Enjoy a dynamic work environment with opportunities for remote work and career growth.
  • Why this job: Work with massive datasets and cutting-edge technologies to drive impactful business decisions.
  • Qualifications: Experience in SQL, data engineering, and building ETL pipelines is essential.
  • Other info: We value diversity and provide accommodations for applicants with disabilities.

The predicted salary is between 36000 - 60000 Β£ per year.

Are you passionate about data? Does the prospect of dealing with massive volumes of data excite you? Do you want to build data engineering solutions that process billions of records a day in a scalable fashion using AWS technologies? Do you want to create the next-generation tools for intuitive data access? If so, Amazon Finance Technology (FinTech) is for you!

FinTech is seeking a Data Engineer to join the team that is shaping the future of the finance data platform. The team is committed to building the next generation big data platform that will be one of the world\’s largest finance data warehouse 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. Amazon has culture of data-driven decision-making, and demands data that is timely, accurate, and actionable. Our platform serves Amazon\’s finance, tax and accounting functions across the globe.

As a Data Engineer, you should be an expert with data warehousing technical components (e.g. Data Modeling, ETL and Reporting), infrastructure (e.g. hardware and software) and their integration. You should have deep understanding of the architecture for enterprise level data warehouse solutions using multiple platforms (RDBMS, Columnar, Cloud). You should be an expert in the design, creation, management, and business use of large data-sets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. The candidate is expected to be able to build efficient, flexible, extensible, and scalable ETL and reporting solutions. You should be enthusiastic about learning new technologies and be able to implement solutions using them to provide new functionality to the users or to scale the existing platform. Excellent written and verbal communication skills are required as the person will work very closely with diverse teams. Having strong analytical skills is a plus. Above all, you should be passionate about working with huge data sets and someone who loves to bring data-sets together to answer business questions and drive change.

Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big data, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all, is a passionate about data and analytics. In this role you will be part of a team of engineers to create world\’s largest financial data warehouses and BI tools for Amazon\’s expanding global footprint.

Key job responsibilities
β€’ Design, implement, and support a platform providing secured access to large datasets.
β€’ Interface with tax, finance and accounting customers, gathering requirements and delivering complete BI solutions.
β€’ Model data and metadata to support ad-hoc and pre-built reporting.
β€’ Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
β€’ Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
β€’ Tune application and query performance using profiling tools and SQL.
β€’ Analyze and solve problems at their root, stepping back to understand the broader context.
β€’ Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use.
β€’ 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.
β€’ Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
β€’ Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.

BASIC QUALIFICATIONS

– Experience with SQL
– 1+ years of data engineering experience
– Experience with data modeling, warehousing and building ETL pipelines
– Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
– Experience with one or more scripting language (e.g., Python, KornShell)

PREFERRED QUALIFICATIONS

– Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
– Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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, FinOps FP&A, FinOps FP&A employer: Amazon

Amazon Finance Technology (FinTech) is an exceptional employer, offering a dynamic work environment where data-driven decision-making thrives. Employees benefit from a culture that encourages innovation and continuous learning, with ample opportunities for professional growth in the rapidly evolving field of big data. Located at the forefront of technology, Amazon provides a unique chance to work on large-scale data engineering solutions that have a direct impact on global business operations.
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Contact Detail:

Amazon Recruiting Team

StudySmarter Expert Advice 🀫

We think this is how you could land Data Engineer, FinOps FP&A, FinOps FP&A

✨Tip Number 1

Familiarise yourself with AWS technologies, as they are crucial for this role. Consider taking online courses or certifications that focus on AWS data services to demonstrate your commitment and knowledge.

✨Tip Number 2

Network with current or former employees in the FinTech team at Amazon. Engaging with them on platforms like LinkedIn can provide you with insights into the company culture and specific expectations for the Data Engineer role.

✨Tip Number 3

Prepare to discuss your experience with large datasets and ETL processes during interviews. Be ready to share specific examples of how you've solved complex data problems in previous roles.

✨Tip Number 4

Stay updated on the latest trends in big data technologies. Being knowledgeable about tools like Hadoop, Spark, and various ETL solutions will not only help you in interviews but also show your passion for the field.

We think you need these skills to ace Data Engineer, FinOps FP&A, FinOps FP&A

Data Warehousing
ETL Development
SQL
Data Modelling
Big Data Technologies (Hadoop, Hive, Spark)
Data Integration
Business Intelligence Solutions
Performance Tuning
Data Analysis
Python or Scripting Languages
Communication Skills
Problem-Solving Skills
Cloud Technologies (AWS)
Analytical Skills
Documentation and Validation

Some tips for your application 🫑

Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with SQL, data modelling, and ETL pipelines. Use specific examples that demonstrate your ability to handle large datasets and your familiarity with AWS technologies.

Craft a Compelling Cover Letter: In your cover letter, express your passion for data and how it drives decision-making. Mention your experience with big data technologies and your enthusiasm for learning new tools. Be sure to align your skills with the job responsibilities outlined in the description.

Showcase Your Technical Skills: Include a section in your application that lists your technical skills, such as proficiency in SQL, Python, and any big data technologies you have worked with. This will help the hiring team quickly see your qualifications.

Prepare for Potential Questions: Think about how you would answer questions related to your experience with data integrity, problem-solving in ambiguous situations, and your approach to building scalable ETL solutions. Being prepared will help you articulate your thoughts clearly during interviews.

How to prepare for a job interview at Amazon

✨Show Your Passion for Data

Make sure to express your enthusiasm for working with large datasets and data engineering solutions. Share specific examples of projects you've worked on that involved massive volumes of data, and how you tackled challenges in those situations.

✨Demonstrate Technical Expertise

Be prepared to discuss your experience with SQL, data modelling, and ETL pipelines. Highlight any relevant tools or technologies you've used, such as Hadoop or Spark, and be ready to explain how you've applied them in real-world scenarios.

✨Communicate Effectively

Since the role involves interfacing with finance and accounting teams, practice articulating complex technical concepts in a way that non-technical stakeholders can understand. This will showcase your ability to bridge the gap between data engineering and business needs.

✨Stay Updated on Big Data Trends

Research the latest advancements in big data technologies and AWS services. Being knowledgeable about current trends will not only impress your interviewers but also demonstrate your commitment to continuous learning and improvement in the field.

Data Engineer, FinOps FP&A, FinOps FP&A
Amazon
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  • Data Engineer, FinOps FP&A, FinOps FP&A

    London
    Full-Time
    36000 - 60000 Β£ / year (est.)

    Application deadline: 2027-08-01

  • A

    Amazon

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