DESCRIPTION As a Data Engineer in Data Infrastructure and Strategy group, you will play a key role in transforming the way Operations Finance teams access and analyse the data. You will work to advance 3 Year Data Infrastructure Modernisation strategy and build unified data access platform and scalable governance and observability frameworks that follow modern data architecture and cloud-first designs.
Your responsibilities will include ownership over end-to-end implementation of features within the platform: component design, implementation using NAWS services that follows best engineering practices, user acceptance testing, launch, adoption and post-launch support. You will work on system design and integrate new components to established architecture. You will be engaged into cross-team collaboration by building reusable design patterns and components and adopting designs adopted by others. You will contribute to "buy" vs "build" decision by evaluating latest product and features releases for NAWS and internal products, perform gap analysis and define feasibility of their adoption and the list of blockers.
The ideal candidate possess a track record of creating efficient AWS-based data solutions; data models for both relational databases and Glue/Athena/EMR stack; developing solution documentation, project plans, user guides and other project documentation. We are looking into individual contributor inspired to become data systems architects. Track of production level deliverables leveraging GenAI is big plus.
Key job responsibilities
* Execute projects against data platform roadmap epics and work streams using AWS technologies and internally built tools, including Spark/EMR, Redshift, Athena, DynamoDB, Lambda, S3, Glue, Lake Formation, etc;
* Contribute into engineering excellence by reviewing design and code created by others;
* Support adoption by both, finance and technical teams; identify and remove adoption blockers;
* Collaborate with a wide range of stakeholders, including FGBS, BDT, and AWS PLUS technology partners, product and engineering teams in S&A, as well as the leadership team, to deliver modern technology-driven data solutions aligned with S&A strategy;
* Create technical and customer-facing documentation on the products within the platform;
* Perform ongoing product support;
* Moderate travel (
A day in the life
You work with the Engineering, Product, BI and Operations teams to implement best-of-class data solutions across the globe based. You solve unstructured customer pain points with technical solutions, you are focused on users productivity when working with the data. You design, implement and ship solutions using AWS CDK and NAWS services. You operate at systems architecture level, not a pipeline level. You review your design with Principal Engineer, collect and apply gathered insights. You are cognisant of how you work impacts your Customers and build efficient development and change management processes to guarantee speed and quality of the delivery.
About the team
WW Operations Finance Standardization and Automation improves customer experience and business outcomes across Amazon Operations Finance through innovative technical solutions, standardization and automation of processes and use of cutting-edge technology.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Bellevue, WA, USA BASIC QUALIFICATIONS - MS or BS in Computer Science, Electrical Engineering, or similar fields;
- Strong AWS engineering background, 5+ years of demonstrated track record designing and operating data solutions in Native AWS. The right person will be highly technical and analytical with ability to drive technical execution towards organization goals;
- Strong data modelling experience, 5+ years of data modeling practice is required. Expertise in designing both analytical and operational data models is a must. Candidate needs to demonstrate the working knowledge of trade-offs in data model designs and platform-specific considerations with concentration in Redshift, MySQL, EMR/Spark and Athena;
- Excellent knowledge of modern data architecture concepts - data lakes, data lakehouses, - as well as governance practices;
- Strong documentation skills, proven ability to adapt the document to the audience. The ability to communicate the information on levels ranging from executive summaries and strategy addendums to detailed design specifications is critical to the success;
- Excellent communication skills, ability to communicate technical complexity to a wide range of stakeholders;
