Data Engineer II, Seller Pricing & Shared Services

Data Engineer II, Seller Pricing & Shared Services

At Amazon, a large portion of our business is driven by third party Sellers who set their own prices. Are you interested in owning pricing analytics to support the growth and competitiveness of our third party Seller business on Amazon? We are looking for a seasoned Data Engineering to help us support the WW Pricing team. The Pricing team is responsible for the metrics that define price competitiveness, quantify seller experience and customer price perception. We support all Amazon programs and geographies worldwide.

The ideal candidate is a motivated self-starter that can work in a fast paced, ambiguous environment with limited supervision. You must be a fast learner who can quickly absorb the nuances of Amazon's varied pricing programs and processes.

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CORE RESPONSIBILITIES:

1. Architecture design and implementation of next generation data pipelines and BI solutions
2. Manage AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
3. Build and deliver high quality data architecture and pipelines to support business analyst, data scientists, and customer reporting needs.
4. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
5. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

BASIC QUALIFICATIONS

1. 5+ years of data engineering experience
2. Experience with data modeling, warehousing and building ETL pipelines
3. Experience with SQL
4. Knowledge of distributed systems as it pertains to data storage and computing
5. Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam

PREFERRED QUALIFICATIONS

1. Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
2. Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
3. Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

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