7 days ago
London, United KingdomMid Level
Responsibilities
- Design and maintain scalable ETL/ELT pipelines and data models for procurement analytics, supplier mapping, and trusted supplier data.
- Create logical and physical data models across large, multi-source datasets while ensuring data quality and consistency.
- Build self-service data infrastructure and curated datasets for business intelligence engineers, scientists, and business teams.
- Collaborate with engineering, science, product, program, and business stakeholders to turn requirements into documented, high-performing data solutions.
- Evaluate generative AI tooling for data workflows and contribute to the team’s AI transformation efforts.
- Build, improve, and operate data solutions while participating in design reviews, sprint ceremonies, and cross-time-zone collaboration.
Requirements
- Experience as a data engineer or related specialty with a track record of manipulating, processing, and extracting value from large datasets.
- Experience independently delivering end-to-end projects.
- Experience with data modeling, data warehousing, and ETL pipelines.
- Experience with SQL and databases such as Redshift, Oracle, or NoSQL systems.
- Programming experience with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, or Ruby.
- Knowledge of professional software engineering practices across the software development lifecycle, including coding standards, software architecture, code reviews, source control, continuous deployments, testing, and operational excellence.
- Preferred experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
- Preferred experience with non-relational data stores, highly available distributed data extraction and processing systems, and big data technologies such as Hadoop, Hive, Spark, or EMR.
Benefits
- The role provides dedicated heads-down work time balanced with regular collaboration across EU and North American time zones.
- Employees participate in an agile squad with sprint ceremonies, design reviews, and cross-functional collaboration.
- The team offers opportunities to grow across software, data, and AI engineering disciplines.
- Amazon provides workplace accommodations or adjustments during the interview and hiring process when needed.
Categories
Data Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.