Data Engineer, FinAuto, Confluence

Description Are you interested in building the next generation cloud-based highly scalable analytics platform that can handle hundreds of billions of dollars in transactions? Our challenge is to deliver software systems that can accurately capture, process, and report on the enormous volume of financial transactions generated every day as millions of customers make purchases, as thousands of Vendors and Partners are paid, as inventory moves in and out of warehouses, as commissions are calculated, and as taxes are collected in hundreds of jurisdictions worldwide. This is a unique opportunity to be part of a team building a cloud-native data ingestion services and platform. The platform will leverage the latest big data technologies to ingest, store, govern and share the data securely.

Candidate Should Have Strong understanding of ETL concepts and experience building them with large-scale, complex datasets using traditional or map reduce batch mechanism. Experience designing and operating data lakes Expertise in at least one programming language - Scala, Python, Java or similar. Experience with data orchestration frameworks like Apache Airflow Good to have - experience working on AWS stack Clear thinker with superb problem-solving skills to prioritize and stay focused on big needle movers Key job responsibilities Looking for a candidate to design, develop, and maintain scalable data solutions on AWS. The ideal candidate will have hands-on experience building robust data pipelines and ETL workflows using services such as AWS Glue, Lambda, Step Functions, and EMR. Familiarity with data catalog tools like AWS DataZone or other products, as well as open table formats like Apache Hudi and Iceberg, is highly beneficial. The ideal candidate will have extensive experience in dimensional modeling, excellent problem solving ability dealing with huge volumes of data and a strong curiosity to learn and adapt to new technologies. You will collaborate with cross-functional teams to understand business requirements, architect scalable data solutions, and ensure data quality and integrity.

About The Team Foundational Data Services (FDS) designs, builds, and maintains a petabyte-scale data lake and a modern data mesh that forms the foundation of data-driven innovation for Finance operations at Amazon. This platform supports hundreds of teams across engineering, science, and business intelligence, enabling them to unlock the full potential of machine learning and advanced analytics. Our mission is to empower FinOps through seamless access to data by delivering a comprehensive suite of solutions focused on efficient data ingestion and storage, strong data governance, and dependable data delivery. If you're passionate about creating scalable, high-impact data solutions that drive financial operations, we’d love to have you on our team!

Basic Qualifications

• 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.

Company - ADCI HYD 13 SEZ Job ID: A10440111