Data Engineer II, PPE Product Intelligence

Requirements

• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• Experience with data modeling, warehousing and building ETL pipelines
• Bachelor's degree
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Experience creating processes and improving tools that have measurably improved productivity, quality, or advertiser experience
• Experience in creating process improvements with automation and analysis, or experience in identifying, leading, and executing opportunities to improve, automate, standardize or simplify finance or business tools and processes
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually

Additional Information

Amazon's Price Perception and Evaluation team is seeking a driven Data Engineer to work on exciting price evaluation projects. As a Data Engineer, you will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in machine learning models and ad-hoc data requests. You will be exposed to AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and applied scientists to gather infrastructure requirements, design data infrastructure, build up data pipelines and datasets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate. Key job responsibilities - Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc. - Develop and manage ETLs to source data from various systems and create unified data model for machine learning models. - Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency. - Working closely with a team of scientists to drive price evaluation model research. - Manage numerous requests concurrently and strategically, prioritizing when necessary

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