Data Engineer, Amazon Stores FinTech

Amazon is hiring a Data Engineer, Amazon Stores FinTech. Level rates it ; you can apply on Level.

AI in this role

Are you passionate about standardizing data platforms and automating data engineering to drive analytics and reporting? Do you excel in dynamic, fast-paced environments and find joy in converting data into actionable insights? Are you adept at implementing data governance practices and defining data access and quality standards? If you thrive in innovation and can deliver scalable Data Engineering Solutions, then the Worldwide Operations Finance Standardization & Automation (S&A) team has an exciting opportunity for you! We are seeking a customer-centric Data Engineer to establish a reliable and accessible data platform, ensuring Operations Finance customers have complete trust in the data, technology, and tools to make data-driven business decisions. We are looking for a Data Engineer to be part of our Global Data Delivery organization, working with one of the world's largest and most complex data warehouse environments.

As a Data Engineer in WW Ops S&A, you will design, implement and support scalable data infrastructure solutions and implement complex data models for Amazon Customer Fulfillment business. You will create solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, GenAI models and ad-hoc data requests. You should have excellent business and communication skills to be able to work with business owners, Finance and Product teams along with tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You will be responsible for developing and operating a data service platform using Python, Airflow, and SQL to build various ETL, analytics, and data quality components. You'll automate deployments using AWS CodeDeploy, AWS CodePipeline, AWS Cloud Development Kit (CDK), and AWS Cloud Formation. You will work with AWS services like Redshift, Glue, S3, IAM, CloudWatch, and more. Strong experience in Data Warehouse and Business Intelligence application development, expert knowledge in SQL query optimization, and experience with programming languages such as Scala/Python are essential for this role.

Key job responsibilities
• Design, build, and maintain complex data solutions and ETL pipelines using Python, Spark, SQL, and AWS services (S3, Glue, Redshift, MWAA, EMR, Lambda)

• Develop high-quality data architecture and scalable pipelines to support customer reporting needs, while implementing and supporting analytics infrastructure for internal Finance customers

• Interface with technology teams to extract, transform, and load data from various sources, ensuring data quality and making appropriate trade-offs in design decisions

• Collaborate with business users, developers, and BI Engineers to deliver on data architecture projects and next-generation financial solutions

• Actively participate in code reviews, design discussions, and team planning, while continually improving reporting processes and automating self-service support

• Identify and implement process improvements to drive innovation, scale existing solutions, and create new ones based on stakeholder needs

• Diagnose and resolve operational issues through detailed root cause analysis, maintaining high standards of system availability and reliability

Basic qualifications

- Experience in data engineering
- Experience with data modeling, warehousing and building ETL pipelines

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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.

How we rate this

Data Engineer, Amazon Stores FinTech at Amazon rates 13 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.