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Form of workDo you have a desire to make a major contribution to the future in the rapid growth environment of Cloud Computing? Are you passionate about data and code? Does the prospect of dealing with massive volumes of data excite you? Do you want to build Data Engineering solutions that process millions of records? Amazon Web Services is looking for a Data Engineer to help build a scalable, secured and robust data infrastructure that supports the AWS Infrastructure services & supply chain Finance (AISSCF) organization. You will be part of the AISSCF Analytics team working with other Data Engineers, Business Intelligence engineers, Product managers and partner with finance/business stakeholders to achieve our goals.
AWS Infrastructure and Supply chain Finance is seeking a Data Engineer to join the team that is building data infrastructure to support analytical and operational finance requirements. The team is committed to building the next generation data platform that will enable support for Amazon's rapidly growing and dynamic businesses, and use it to deliver the BI applications which will have an immediate influence on day-to-day decision making. Amazon has culture of data-driven decision-making, and demands data that is timely, accurate, and actionable. Our platform serves Amazon's finance, supply chain and accounting functions across the globe. You will be primarily using but not limited to AWS solution stacks like Redshift, S3, Lambda, SNS/SQS, Lake-formation, Data Pipelines (AWS Glue/Hammerstone) and reporting tools such as Tableau and Alteryx to implement BI solutions.
As a Data Engineer, you should be an expert with data warehousing technical components (e.g. Data Modeling, ETL and Reporting), infrastructure (e.g. hardware and software) and their integration. You should have deep understanding of the architecture for enterprise level data warehouse solutions using multiple platforms (RDBMS, Columnar, Cloud). You should be an expert in the design, creation, management, and business use of large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. The candidate is expected to be able to build efficient, flexible, extensible, and scalable ETL and reporting solutions. You should be enthusiastic about learning new technologies and be able to implement solutions using them to provide new functionality to the users or to scale the existing platform. Excellent written and verbal communication skills are required as the person will work very closely with diverse teams. Having strong analytical skills is a plus. Above all, you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.
Our ideal candidate thrives in a fast-paced environment, relishes working with large transactional data volumes, enjoys the challenge of highly complex business contexts (that are typically being defined in real-time), and, above all, is a passionate about data and analytics.
Key job responsibilities
Design, implement, and support a platform providing secured access to large datasets.
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
Tune application and query performance using profiling tools and SQL.
Analyze and solve problems at their root, stepping back to understand the broader context.
Learn and understand a broad range of Amazon's data resources and know when, how, and which to use and which not to use.
Keep up to date with advances in data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS.
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.
Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA | Seattle, WA, USA
