Job summary
Have you ever wondered how is Amazon able to scale retail business across thousands of vendors? Are you curious about the architecture that supports millions on contributions and vendor experiences across all channels? Do you want to spearhead an impactful and innovative space to create value for Retail customers, and Vendors, who rely on Amazon to grow their businesses?
Our team applies science and technology to manage contributions at scale, enabling suppliers to offer products to buyers (Amazon). We develop architecture to support billions in contributions towards amazon selection, at scale, through tens of channels. We apply science to 1.) identify and eliminate errors in contributions, and 2.) identify sub-optimal contracts at creation time and improve profitability. We develop consistent experiences for internal users (vendor managers) and suppliers throughout the process.
We own a critical intersection between vendor contribution, procurement and pricing workflows creating a high impact on Amazon selection, retail customer experience, vendor experience and vendor manager experience. We own the transactional systems which are the backbone of Amazon Supply Chain, and plays a crucial role in ensuring Amazon is able to procure inventory. We own tier-1 systems which support the creation of Amazon’s offer for end customers. We support teams across SPS, SCOT and NACL organizations.
Key job responsibilities
In this role, you will be a technical expert with significant scope and impact. You will work closely with a group of Software Development Engineers, Product Managers, Scientists, and Business Intelligence Engineers to create the data infrastructure and pipelines necessary to drive our team’s initiatives.
Our Data Engineer duties & responsibilities will include:
Design and deliver big data architectures for experimental and production consumption between scientists and software engineering
Develop the end-to-end automation of data pipelines, making datasets readily-consumable by visualization tools and notification systems.
Create automated alarming and dashboards to monitor data integrity.
Create and manage capacity and performance plans.
Act as the subject matter expert for the data structure and usage.
BASIC QUALIFICATIONS
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
4+ years of industry experience in Software Development, Data Engineering, Business Intelligence or related field with a solid track record of manipulating, processing, and extracting values from large datasets.
Experience with data modeling, data warehousing, and building ETL pipelines
Solid experience using big data technologies (Redshift, Hadoop, Hive, Hbase, Spark, EMR, etc.).
Skilled with writing, tuning, and troubleshooting SQL queries
Experience in designing and building scalable data pipelines
Excellent grasp of software development life cycle and/or agile development environment
Knowledge and experience with Data Management and Data Storage best practices.
Strong customer focus, ownership, and ability to deliver results.
Excellent communication and collaboration skills
Effective analytical, troubleshooting, and problem-solving skills.
PREFERRED QUALIFICATIONS
Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
Experience working with AWS big data technologies (Redshift, S3, EMR, Glue).
Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
Experience providing technical leadership and educating other engineers for best practices on data engineering.
Background in Big Data, non-relational databases, Machine Learning and Data Mining is a plus.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
Associated topics: data administrator, data analytic, data center, data engineer, data manager, data warehousing, hbase, mongo database, mongo database administrator, teradata