Data Engineer

Amazon
Amazon

Job Overview

DESCRIPTION

Are you excited about driving business growth for millions of sellers through application of Machine Learning and other advanced computer science disciplines? Do you thrive in a fast-moving, large-scale environment that values data-based actions, robust engineering, and sound scientific practices? We’re looking for a proven Data Engineer who can take the Selling Partner experience to the next level: shaping the roadmap, working with scientists and engineers to define solutions, and integrating these efforts into a coherent product. Our ideal candidate has great insight into our customers (and the data skills to develop these insights), the vision and creativity to find innovative ways to act on these insights, the technical chops to translate those ideas into innovative design, and interpersonal skills to harness the passion and energy of teams across the company to drive the designs into the world as products that will delight our customers.
In this role, you will work closely with scientists, software engineers, stakeholders, and product teams across Amazon to drive large cross-org innovations and project delivery activities.
As an Amazon.com Data Engineer you will be working in one of the world’s largest and most complex data warehouse environments. The team will look to you for advice on analytical and business issues facing them. You work very efficiently and routinely deliver the right things. You will have a company-wide view of the analytical solutions that you build, and you will consistently think in terms of automating or expanding the results company-wide. This high impact role will have an opportunity to design and build our data infrastructure from the ground up, work with emerging technologies such as Redshift, Andes, Datanet, Cradle & QuickSight, while driving business intelligence solutions end-to-end: business requirements, workflow instrumentation, data modeling, ETL, metadata, reporting, and dashboard development. He/she should be an expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. The role requires someone who loves data, understands enterprise information systems, has a strong business sense, and can manage to put these skills into action.

Responsibilities
• Conduct deep dive investigations into business problems, identify potential opportunities and formulate conclusions and recommendations to be presented to senior management
• Support and demand your team to meet critical milestones
• Own the design, development and support a scalable, reliable infrastructure for Data Warehousing and Business Intelligence and maintain data pipelines using various technologies (e.g. AWS Redshift, Amazon Internal ETL tools) to drives computing key business metrics
• Own the design, development of reports and dashboards using various technologies (e.g. QuickSight, Amazon Internal Reporting tools) to allow internal teams (technology, product management, operations teams) to understand issues and identify actions to be taken to solve these business problems
• Identify ways to automate data pipelines and dashboards through smarter software systems

BASIC QUALIFICATIONS

· Bachelor’s or Master’s degree in Computer Science or related fields
· 5+ years of relevant experience in one of the following areas: Data Engineering, Database Engineering, Business Intelligence Engineering
· 5+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets
· Demonstrated strength in data modeling, ETL development, and Data warehousing
· Experience with AWS services including S3, Redshift.
· Experience in working and delivering end-to-end projects without supervision
· Knowledge of distributed systems as it pertains to data storage and computing

PREFERRED QUALIFICATIONS

· Demonstrated industry standards in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing
· Experience providing technical guidance to other engineers for best practices on Data Engineering
· Deep understanding of data, application, server, and network security
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Advanced knowledge and expertise with Data modelling skills, Advanced SQL with Oracle, MySQL, and Columnar Databases
· Experience with AWS service QuickSight

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