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Amazon
Are you driven by innovation? Is collaborative problem-solving your forte? Do you relish the idea of witnessing the ripple effects of your contributions in a grander context? If any of these resonate with you, then you're destined for success within the vibrant realm of WWGS Data & Analytics. We are a dynamic cohort of visionaries who channel our expertise into translating cutting-edge advancements in data and software engineering into real-world solutions that transcend conventional boundaries. We shape novel improvements every day, and now we invite you to be part of our pioneering narrative. Welcome to WWGS Data & Analytics, where we equip you with the tools and camaraderie you need to forge inventive pathways that are not just professionally fulfilling, but also incredibly enjoyable.
Our team of Data engineers, Business Intelligence engineers, business analysts, and software engineers form the backbone of our business operations, enabling us to make informed decisions powered by data. As an Amazon Data Engineer, you will find yourself navigating the sprawling landscape of one of the amazon's largest data warehouses. Our enthusiasm lies in constructing a remarkably scalable big data ecosystem that bolsters our analytics, machine learning, and data-driven applications.
Key job responsibilities
- Architecture design and implementation of next generation data pipelines and BI solutions
- Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda, Glue, Apache Airflow etc.
- Build and deliver high quality data architecture and pipelines to support business analyst, data scientists, and customer reporting needs.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
A day in the life
As a WWGS Data & Analytics Data Engineer, you will help tackle a diverse landscape of technical challenges. You will partner with other Software Engineers along with Data Engineers, Business Intelligence Engineers, Analysts, Product Manager, and Program Managers inside and outside of the team to distill large, complicated datasets into automated, digestible analytic deliverables. You will play an active role in translating business requirements into concrete systems and prototyping concepts in partnership with Amazon, technology leaders within the team and across the business.
You will design, develop and deploy reliable distributed solutions that operate at Amazon scale. You will work with a variety of core languages and technologies including SQL, Python, Scala and AWS services. You will tackle challenging, novel situations every day and will have the opportunity to redefine an industry while working with different teams across Amazon and WWGS Data & Analytics. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on many people. Most importantly you’ll be contributing to our Higher Purpose of Nourishing People and the Planet!
About the team
We enable sophisticated, fact-based decision making across WWGS Data & Analytics by delivering constantly evolving technology and analytic capabilities. This team will solve challenging and novel problems every day and have the opportunity to redefine the grocery industry while collaborating with multiple teams across WWGS Data & Analytics and Amazon. - A Bachelor's degree or higher in a quantitative/technical field, such as Computer Science, Statistics, or Engineering.
- 3+ years of data engineering experience.
- Profound experience in designing, implementing, and overseeing data processing systems tailored for extensive datasets.
- Proficiency in at least one modern programming language, whether it's Java, Scala, or Python.
- Hands-on expertise and advanced comprehension of SQL.
- A firm grasp of data management fundamentals and principles underpinning data storage.
- Proficiency in the realm of distributed systems as they pertain to data storage and cloud computing.
- A proven track record of working with Open-Source Big Data tools, including Hadoop, Spark, Hive, and Presto, among others.
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