Manager III, Data Engineering - AMZ9084866

Amazon • Seattle, WA

63d • $170,000 - $230,000

About The Position

Lead team to design, implement, and operate large-scale, high-volume, high-performance data structures for analytics and data science. Implement data ingestion routines, real time and batch, using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation. Collaborate with scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning. Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers. Hire, manage, and develop team members.

Requirements

• Master’s degree or foreign equivalent degree in Computer Science, Statistics, Engineering, or a related field and three years of experience in the job offered or a related occupation.
• Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Statistics, Engineering, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master’s degree and three years of experience.
• Must have two years of experience in the following skills: 1) data modeling, data warehousing, and building ETL pipelines; 2) using SQL; 3) hands-on experience in writing complex, highly-optimized SQL queries across large data sets; 4) using Microsoft Office and at least one modern scripting or programming language, such as Python, Perl, Ruby, Scala, or NodeJS; 5) experience in ETL development; 6) experience with massively parallel processing (MPP) databases, data warehouse and data lake; 7) using Tableau, ETL, and AWS services including with Redshift, S3, AWS Glue, EMR, or DynamoDB; 8) using cloud data platforms and big data solutions; 9) managing data pipelines and processing software development; and 10) hiring, managing teams, and coaching performance.

Nice To Haves

• Please see job description and the position requirements above.

Responsibilities

• Lead team to design, implement, and operate large-scale, high-volume, high-performance data structures for analytics and data science.
• Implement data ingestion routines, real time and batch, using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
• Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
• Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.
• Collaborate with scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.
• Hire, manage, and develop team members.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager