Data Engineer

Amazon.com Services, Inc.
 Tempe, AZ

Desciption

Job summary

Our team is passionate about Brands who sell on Amazon - we help them grow their businesses, build their story, and serve their customers. How do we do this? Data! Help us serve this valuable data to our Brands in digestible ways so they can run their businesses more effectively.

The ideal candidate will have excellent problem investigation abilities, and the ability to synthesize data into crisp and clear recommendations for scientists and product leaders. To be successful in this role, you should have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business needs.

In the role, you will work closely with scientists, product managers and software engineers to build out infrastructure, data pipelines, and reporting mechanisms for our team and our Brands.

Our Data Engineer duties & responsibilities will include:

· Design and deliver big data architectures for experimental and production consumption between scientists and software engineering

· Develop the end-to-end automation of data pipelines, making datasets readily-consumable by visualization tools and notification systems.

· Create automated alarming and dashboards to monitor data integrity.

· Create and manage capacity and performance plans.

· Act as the subject matter expert for the data structure and usage.

Basic Qualifications

· - 5+ 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

· Excel in the design, creation, and management of very large datasets

· Skilled with writing, tuning, and troubleshooting SQL queries

· Experience with Big Data technologies such as Hive, Spark, Hadoop, NoSQL, AWS EMR, Glue, Lambda, Kinesis, Redshift

· Proficiency with Python, Java, or Scala (Scala preferred)

· Excellent grasp of software development life cycle and/or agile development environment

· Strong organizational and planning skills with attention to detail

· Experience in understanding system limitations, scaling factors, boundary conditions, and the reasons for architectural decisions

· Experience in Designing and building scalable data pipelines

Preffered Qualifications

· - 7-10 years of industry experience as a Data Engineer or related specialty (e.g. Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets

· Detailed knowledge of data warehouses, architecture, infrastructure components, ETL and reporting tools and environments

· Experience with orchestration tools such as Step Functions or Airflow (Airflow preferred).

· Experience with Massively Parallel Processing (MPP) databases - Redshift, Teradata etc.

· Experience with distributed systems and NoSQL databases

· Experience directing medium to large-scale data warehousing and BI projects, including using AWS technologies – Redshift, S3, EC2, Data-pipeline and other big data technologies

· Excellent communication skills and able to work with business owners to develop and define key business questions and to build data sets that answer those questions

· Experience providing technical direction and mentorship of engineers and scientists on best practices in the data engineering space

· Comfort working with the Linux command line

· Be self-motivated and show ability to deliver on ambiguous situations and projects

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.

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