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

Amazon; London; On-site; GBP 50,000 - 90,000; Full time

Job summary

An established industry player is seeking a passionate Data Engineer to join their innovative team. This role involves building scalable data engineering solutions that process massive volumes of data daily using cutting-edge AWS technologies. You'll design and maintain a robust data architecture, enabling the creation of the world's largest financial data warehouses. If you're enthusiastic about data and analytics, and thrive in a fast-paced environment, this opportunity offers the chance to make a significant impact on decision-making processes across a global organization.

Qualifications

• 1+ years of data engineering experience with a focus on ETL and data modeling.
• Strong understanding of SQL and experience with big data technologies.

Responsibilities

• Design and support a platform for secure access to large datasets.
• Interface with finance and accounting to deliver complete BI solutions.
• Model data to support reporting and drive key business decisions.

Skills

SQL

Data Engineering

Data Modeling

ETL Pipelines

Python

Analytical Skills

Education

Bachelor's Degree in Computer Science or related field

Tools

Hadoop

Spark

Informatica

Job description

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? If so, Amazon Finance Technology (FinTech) is for you!

About FinTech

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, which will be one of the world's largest finance data warehouses, supporting Amazon's rapidly growing and dynamic businesses. This platform will enable the delivery of BI applications that influence day-to-day decision making. Amazon values a culture of data-driven decision-making, requiring data that is timely, accurate, and actionable. Our platform serves Amazon's finance, tax, and accounting functions globally.

Role Overview

As a Data Engineer, you should be an expert in data warehousing components (e.g., Data Modeling, ETL, Reporting), infrastructure (hardware and software), and their integration. You should have a deep understanding of enterprise data warehouse architecture across multiple platforms (RDBMS, Columnar, Cloud). The role involves designing, creating, managing, and utilizing large data sets, and working closely with business owners to develop data solutions that answer key business questions. You should be enthusiastic about learning new technologies and implementing solutions to enhance platform functionality or scalability. Excellent communication skills are essential, as well as a strong analytical mindset and a passion for working with large data sets to drive business insights.

Key Responsibilities

1. Design, implement, and support a secure platform for large datasets.
2. Collaborate with tax, finance, and accounting teams to gather requirements and deliver BI solutions.
3. Model data and metadata to support reporting needs.
4. Develop and maintain metrics, reports, dashboards to inform business decisions.
5. Adopt best practices in data integrity, testing, validation, and documentation.
6. Optimize application and query performance using profiling tools and SQL.
7. Analyze problems deeply and understand the broader context.
8. Familiarize with Amazon’s data resources and determine appropriate usage.
9. Stay updated on big data technologies, run pilots, and design scalable data architectures on AWS.
10. Improve reporting and analysis processes, automate and support self-service data access.
11. Make informed decisions in high-ambiguity environments, balancing quantitative analysis and business judgment.

Basic Qualifications

• Experience with SQL
• At least 1 year of data engineering experience
• Experience with data modeling, warehousing, and ETL pipelines
• Proficiency in query languages like SQL, PL/SQL, HiveQL, SparkSQL, Scala
• Experience with scripting languages such as Python or KornShell

Preferred Qualifications

• Experience with big data technologies like Hadoop, Hive, Spark, EMR
• Experience with ETL tools such as Informatica, ODI, SSIS, BODI, DataStage

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need accommodations during the application or onboarding process, please visit this link. For country-specific inquiries, contact your Recruiting Partner.

Posted Dates: Multiple dates ranging from March to May 2025, with recent updates noted.

Amazon is an equal opportunity employer and does not discriminate based on protected statuses.