Sr. Data Engineer

Sunnyvale, California, USA

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Job summary
We are seeking a talented, self-directed Data Engineer to design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for our internal customers. Implement data structures using best practices in data modeling and ETL/ELT processes. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions that work well within the overall data architecture. Analyze source data systems and drive best practices in source teams. Participate in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance. Produce comprehensive, usable dataset documentation and metadata. Evaluate and make decisions around dataset implementations designed and proposed by peer data engineers. Evaluate and make decisions around the use of new or existing software products and tools. Mentor junior data engineers.

The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. He/she is an expert with data modeling, ETL design and business intelligence tools and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates out-sized business impact. He/she is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail) and enjoys working in a fast-paced team. The ideal candidate needs to possess exceptional technical expertise in large scale data warehouse and BI systems with hands-on knowledge on SQL, Distributed/MPP data storage, and AWS services (S3, Redshift, EMR, RDS).

Key job responsibilities
Design, implement, and support a platform providing ad hoc access to large datasets

Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL

Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL, and Redshift

Build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark

Build and deliver high quality datasets to support business analysis and customer reporting needs

Interface with business customers, gathering requirements and delivering complete data structures

A day in the life
This is an opportunity to get in on the ground floor of a new team in Device Operations. Come join the Product/Program Operations/Research Data/Infrastructure/UX Management (PODIUM) team to fulfill our vision of enabling customer success by building world-class scalable and innovative solutions that anticipate Original Equipment Manufacturer needs and optimizes decision-making throughout the product life cycle.

About the team
PODIUM (Product/Program Operations Research Data Infrastructure UX Management) team consists of related but divergent teams focused on delivery of business driven software and data. The PODIUM team is comprised of data engineers, operations research scientists, user experience designers, product managers, and program managers. This first org-wide group provides an end-to-end perspective of the software (SW) needs of Device Operations and works to ensure that SW designed and built for the entire org are solving both the challenges of today and tomorrow.

Basic Qualifications


· Bachelor's degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering).
· 7+ years of relevant experience in one of the following areas: Data engineering, database engineering, business intelligence or business analytics.
· 7+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.
· 7+ years of experience in scripting languages like Python etc.
· Demonstrated strength in data modeling, ETL development, and data warehousing.
· Experience with Redshift, Oracle, NoSQL, etc.
· Experience with AWS services including S3, Redshift, EMR, Kinesis and RDS.
· Experience in working and delivering end-to-end projects independently.
· Knowledge of distributed systems as it pertains to data storage and computing

Preferred Qualifications

· 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 mentoring other engineers for best practices on data engineering
· Knowledge of software engineering best practices across the development life-cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Masters in computer science, mathematics, statistics, economics, or other quantitative field


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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Architecture AWS Business Analytics Business Intelligence Computer Science Data warehouse Data Warehousing Distributed Systems Economics ELT Engineering ETL Kinesis Mathematics MPP NoSQL Oracle Pipelines Python Redshift Research Spark SQL Statistics Testing UX

Region: North America
Country: United States
Job stats:  5  0  0
Category: Engineering Jobs

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