Data Engineer, Pricing and Promotions Science Data and Insights

Description

Are you passionate about developing the next generation of data infrastructure capable of handling complex, mission-critical data pipelines and analytics workloads? Do you want to build next generation data engineering solutions that leverage the latest AWS technologies to process a broad range of business and customer data?

Join our Pricing & Promotions Science, Data and Insights team, where you'll have the opportunity to continuously improve the systems that enable Amazon's annual worldwide revenue of billions of dollars.

Key job responsibilities

• Design, build, and operate highly scalable, fault-tolerant data processing systems using modern AWS services like Redshift, S3, Glue, EMR, Kinesis, and Lambda, and orchestration systems using Airflow
•  Leverage your expertise in Python, Scala, or other modern programming languages to develop custom data processing frameworks and automation tools
• Collaborate closely with data scientists, analysts, and product managers to understand business requirements and translate them into technical solutions
• Continuously optimize data pipeline performance, reliability, and cost-efficiency using best practices in CI/CD and infrastructure-as-code
• Mentor junior engineers and share your knowledge of data engineering best practices
• Stay up-to-date with the latest big data technologies and architectural patterns, and drive the adoption of innovative solutions

A day in the life

You will:

•  Identify key areas of concerns/limitations with current architecture and build next generation frameworks and systems that enable data teams to deliver on future needs
• Build automated data quality monitoring, audit and reconciliation mechanisms
• Develop and maintain core infrastructure and services for multiple data engineering teams
•  Improve efficiency of operations in terms of cost, effort and reliability

About the team

The Pricing and Promotions Science Data and Insights Org strives to accelerate Customer, Seller, and overall Amazon success through the proactive development of automated intelligent pricing and promotions science and analytics systems. We facilitate making trustworthy data-driven decision making at scale. We look around corners for both long-term and short-term flywheel causal impacts, and think holistically, from sourcing to CX, and all customer journey touch points in between.

Basic Qualifications

• 4+ years of data engineering experience
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with SQL
• Experience with data audit and reconciliation strategies.
• Experience with data pipeline orchestration frameworks, such as Airflow.
• Experience with streaming data processing technologies.

Preferred Qualifications

• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.