Data Engineer (Level 4), AOP

Amazon is a place where data drives most of our decision-making. Analytics, Operations & Programs (AOP) team is looking for a dynamic data engineer who can be innovative, strong problem solver and can lead the implementation of the analytical data infrastructure that will guide the decision making. As a Data Engineer, you think like an entrepreneur, constantly innovating and driving positive change, but more importantly, you consistently deliver mind-boggling results. Youre a leader, who uses both quantitative and qualitative methods to get things done. And on top of it all, youre someone who wonders "What if?" and then seeks out the solution. This position offers exceptional opportunities to grow their technical and non-technical skills. You have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects.

As a Data Engineer, you are responsible for analyzing large amounts of business data, solve real world problems, and develop metrics and business cases that will enable us to continually delight our customers worldwide. This is done by leveraging data from various platforms such as Jira, Portal, Salesforce. You will work with a team of Product Managers, Software Engineers and Business Intelligence Engineers to automate and scale the analysis, and to make the data more actionable to manage business at scale. You will own many large datasets, implement new data pipelines that feed into or from critical data systems at Amazon.

You must be able to prioritize and work well in an environment with competing demands. Successful candidates will bring strong technical abilities combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership and a drive to solve some of the most challenging data and analytic problems in retail. Candidates must have demonstrated ability to manage large-scale data modeling projects, identify requirements and tools, build data warehousing solutions that are explainable and scalable. In addition to the technical skills, a successful candidate will possess strong written and verbal communication skills and a high intellectual curiosity with ability to learn new concepts/frameworks and technology rapidly as changes arise.

Key job responsibilities
- Design, implement and support an analytical data infrastructure
- Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis
- Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
- Maintain internal reporting platforms/tools including troubleshooting and development. Interact with internal users to establish and clarify requirements in order to develop report specifications.
- Work with Engineering partners to help shape and implement the development of BI infrastructure including Data Warehousing, reporting and analytics platforms.
- Contribute to the development of the BI tools, skills, culture and impact.
- Write advanced SQL queries and Python code to develop solutions

A day in the life
This role requires you to live at the intersection of data, software, and analytics. We leverage a comprehensive suite of AWS technologies, with key tools including S3, Redshift, DynamoDB, Lambda, APIs, Glue. You will drive the development process from design to release.
Managing data ingestion from heterogeneous data sources, with automated data quality checks.
Creating scalable data models for effective data processing, storage, retrieval, and archiving.
Using scripting for automation and tool development, which is scalable, reusable, and maintainable.
Providing infrastructure for self serve analytics and science use cases.
Using industry best practices in building CI/CD pipelines

About the team
AOP (Analytics Operations and Programs) team is missioned to standardize BI and analytics capabilities, and reduce repeat analytics/reporting/BI workload for operations across IN, AU, BR, MX, SG, AE, EG, SA marketplace.

AOP is responsible to provide visibility on operations performance and implement programs to improve network efficiency and defect reduction. The team has a diverse mix of strong engineers, Analysts and Scientists who champion customer obsession.

We enable operations to make data-driven decisions through developing near real-time dashboards, self-serve dive-deep capabilities and building advanced analytics capabilities.

We identify and implement data-driven metric improvement programs in collaboration (co-owning) with Operations teams - 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)