Data Engineer, Amazon Customer Service Data Analytics Support Hub
Amazon · Luxembourg · Data Science
mid
Data Engineer
ic
· Posted Jun 9, 2026
Skills
About this role
Amazon is hiring a mid-level Data Engineer based in Luxembourg. The posting calls out experience with Python, Java, Scala, Flutter.
- Role
- Data Engineer
- Function
- data engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Luxembourg
- Department
- Data Science
- Posted
- Jun 9, 2026
Job description
from Amazon careersAmazon's Customer Service (CS) department is seeking an experienced Data Engineer to join the Data Analytics Support Hub (DASH) Advanced Analytics team. CS is the heart of Amazon; our vision is to be Earth's most customer-centric company. The successful candidate will be a key member of the Advanced Analytics branch within DASH, which is evolving Q&E from descriptive ("what happened") to diagnostic and predictive analytics at worldwide
As a Data Engineer II, you will build and own the production data infrastructure that turns Q&E domain expertise into scalable diagnostic and predictive analytics. You will own end-to-end delivery of pipelines for multi-contact journey analytics (Transfers, Repeats, DART, ECR/VPI), transcripts ingestion at WW scale, LLM-serving datasets, and model-serving feature tables. You will also serve as the bridge that connects central data platforms to Q&E-specific, multi-contact journey use cases that central single-touchpoint platforms do not address.
This position can be located in LUX21 or LHR16.
Key job responsibilities
Responsibilities include but are not limited to:
- Build and own production data pipelines for Q&E diagnostic and predictive workloads: transcripts ingestion at WW scale, multi-contact threading, journey-grain feature tables, and model-serving datasets.
- Integrate Q&E pipelines with central infrastructure: consume data and tooling, and connect to Data Stream Service (DSS) to move from 24-36 hour validation latencies toward semi real-time signals.
- Own end-to-end data models and pipelines for the new KPI portfolio
- Scale innovations from prototypes into maintainable, certified production pipelines.
- Build the transcripts prototyping infrastructure used by BIEs and Data Scientists: scalable, secure, App-Security-red-certified, with templates and tooling that reduce new ad-hoc request time-to-delivery.
- Productionize LLM-based diagnostic outputs into reliable datasets that power WBR "why" automation and self-service dive-deeps.
- Own dataset quality, lineage, freshness SLAs, backfills, and alerting. Drive Shepherd risk remediation, App Security reviews, Kale, Legal, Threat Models, DI diagrams, and ASR certification for production deployment.
- Perform code reviews in CRUX; follow Brazil/Apollo/Pipelines best practices; contribute to DE engineering standards and the reusable-components knowledge repository.
- Experience with data modeling, warehousing and building ETL pipelines
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Experience working on and delivering end to end projects independently
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
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 (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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.
As a Data Engineer II, you will build and own the production data infrastructure that turns Q&E domain expertise into scalable diagnostic and predictive analytics. You will own end-to-end delivery of pipelines for multi-contact journey analytics (Transfers, Repeats, DART, ECR/VPI), transcripts ingestion at WW scale, LLM-serving datasets, and model-serving feature tables. You will also serve as the bridge that connects central data platforms to Q&E-specific, multi-contact journey use cases that central single-touchpoint platforms do not address.
This position can be located in LUX21 or LHR16.
Key job responsibilities
Responsibilities include but are not limited to:
- Build and own production data pipelines for Q&E diagnostic and predictive workloads: transcripts ingestion at WW scale, multi-contact threading, journey-grain feature tables, and model-serving datasets.
- Integrate Q&E pipelines with central infrastructure: consume data and tooling, and connect to Data Stream Service (DSS) to move from 24-36 hour validation latencies toward semi real-time signals.
- Own end-to-end data models and pipelines for the new KPI portfolio
- Scale innovations from prototypes into maintainable, certified production pipelines.
- Build the transcripts prototyping infrastructure used by BIEs and Data Scientists: scalable, secure, App-Security-red-certified, with templates and tooling that reduce new ad-hoc request time-to-delivery.
- Productionize LLM-based diagnostic outputs into reliable datasets that power WBR "why" automation and self-service dive-deeps.
- Own dataset quality, lineage, freshness SLAs, backfills, and alerting. Drive Shepherd risk remediation, App Security reviews, Kale, Legal, Threat Models, DI diagrams, and ASR certification for production deployment.
- Perform code reviews in CRUX; follow Brazil/Apollo/Pipelines best practices; contribute to DE engineering standards and the reusable-components knowledge repository.
Basic Qualifications
- Experience in data engineering- Experience with data modeling, warehousing and building ETL pipelines
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
Preferred Qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions- Experience working on and delivering end to end projects independently
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
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 (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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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