Data Engineer II

Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV, Amazon Echo and Amazon Show. The Amazon Devices group delivers delightfully unique Amazon experiences, giving customers instant access to everything, digital or physical.

A day in the life
Specifically, the Data Engineer will:
· Design, implement, and support a platform providing ad hoc access to large datasets (eg data visualization tools for non-tech business users)
. Interface with business customers, gathering requirements and delivering complete reporting solutions.
· 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, developing and delivering complete data structures.
· Manage and design a business intelligence reporting platform integrated to internal and external Amazon systems
· Own the design, development, and maintenance of ongoing Quality metrics, reports, analyses, dashboards, etc. to drive key business decisions.



About the hiring group
Quality Business Intelligence team within Amazon Devices Quality is responsible for designing and architecture of data systems with pipelines, reports, and dashboards that can be scaled to support various business needs. The team is responsible for providing actionable performance metrics in a format that is easy to digest at the highest levels in the organization. These business metrics highlight areas of risk and opportunity, performance outliers, and assist in making well-informed, data-based business decisions. Using this information, we will help business leaders develop a strategy on what company-wide investments to make and the level of their importance.

Job responsibilities
The Role:

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.

You should be an expert in data modeling, ETL design and business intelligence reporting and dashboarding solutions used by thousands of users worldwide. You will passionately partner with the business to identify strategic opportunities where improvements in data infrastructure creates outsized business impact. You are 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, BI systems, and reporting with hands-on knowledge on SQL, Distributed/MPP data storage, and AWS services (S3, Redshift, EMR, RDS). An ideal candidate will have excellent communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. Above all, you should bring your passion for working with huge data sets and bringing datasets together to answer business questions and drive change.



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.

Basic Qualifications

· 3+ years of experience as a Data Engineer or in a similar role
· Experience with data modeling, data warehousing, and building ETL pipelines
· Experience in SQL
· Bachelor's degree in Computer Science, Computer Engineering, Business Administration, Mathematics or a related field
· 5+ years of industry experience as a Data Engineer or related specialty (e.g., Business Intelligence Engineer, Data Scientist)
· 5+ years of hands-on experience in writing complex, highly-optimized queries across large data sets
· Proficiency with data querying or modeling technique with SQL
· Experience delivering automated reports using reporting or data visualization tools such as Tableau, Quicksight, etc.
. Experience defining and driving a BI roadmap, working and delivering end-to-end projects independently.
· 2+ years of experience in scripting languages like Python etc.
· Experience with data modeling, data warehousing, and building ETL pipelines
· Data Warehousing Experience with Oracle, Redshift, Teradata, etc.
· Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
· Experience in continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
· Experience building data products incrementally and integrating and managing datasets from multiple sources
· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets

Preferred Qualifications

· Experience leveraging Python, R or Matlab to manipulate data and set up automated processes as per business requirements
· Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
· Experience leading large-scale data warehousing and analytics projects, including using AWS technologies – Redshift, S3, EC2, Data-pipeline and other big data technologies
· Strong ability to interact, communicate, present and influence within multiple levels of the organization
· Track record of manipulating, processing, and extracting value from large datasets
· Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
· Masters in computer science, mathematics, statistics, economics, or other quantitative fields.