Data Engineer, MIDAS, Digital Acceleration

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OverviewData Engineer, MIDAS, Digital AccelerationAre you excited about the digital media revolution and passionate about designing and delivering advanced analytics that directly influence the product decisions of Amazon's digital businesses. Do you see yourself as a champion of innovating on behalf of the customer by turning data insights into action?The Amazon Digital Acceleration (DA) org is looking for an analytical and technically skilled data engineer to join our team. In this role, you will play a critical part in developing foundational analytical datasets spanning orders, subscriptions, discovery, promotions, pricing and royalties. Our mission is to enable digital clients to easily innovate with data on behalf of customers and make product and customer decisions faster.An ideal individual is someone who has deep data engineering skills around ETL, data modeling, database architecture and big data solutions. This individual should have strong business judgement, excellent written and verbal communication skills.Key responsibilitiesDevelop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (Datanet, Cradle, QuickSight etc.).Improve existing solutions/build solutions to improve scale, quality, IMR efficiency, data availability, consistency & compliance.Partner with Software Developers, Business Intelligence Engineers, MLEs, Scientists, and Product Managers to develop scalable and maintainable data pipelines on both structured and unstructured (text based) data.Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations.About the teamThe MIDAS team operates within Amazon's Digital Analytics (DA) engineering organization, building analytics and data engineering solutions that support cross-digital teams. Our platform delivers a wide range of capabilities, including metadata discovery, data lineage, customer segmentation, compliance automation, AI-driven data access through generative AI and LLMs, and advanced data quality monitoring. Today, more than 100 Amazon business and technology teams rely on MIDAS, with over 20,000 monthly active users leveraging our mission-critical tools to drive data-driven decisions at Amazon scale.Basic QualificationsBachelor's degree3+ years of data engineering experience3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experienceExperience with data modeling, warehousing and building ETL pipelinesExperience working on and delivering end to end projects independentlyExperience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJSPreferred Qualifications5+ years of data engineering experienceExperience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissionsExperience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)Knowledge of Engineering and Operational Excellence using standard methodologies.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.Posted: September 29, 2025 (Updated 1 day ago)Posted: September 26, 2025 (Updated 2 days ago)Posted: September 30, 2025 (Updated 2 days ago)Posted: September 30, 2025 (Updated 2 days ago)Posted: September 29, 2025 (Updated 3 days ago)Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. #J-18808-Ljbffr
Location:
Cambridge, England, United Kingdom
Job Type:
FullTime

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