Data Engineer, Science Tooling And Research (STAR)
North Reading, Massachusetts, USA
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Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...Key job responsibilities
- Implement solutions for data storage, reporting, science and analytics.
- Incorporate big data solutions to enhance machine learning, analytics and reporting capabilities.
- Monitor and troubleshoot operational or data issues in the data pipelines.
- Setup internal dashboard tools for data visualization
- Work across teams to gather requirements for data logging, storing, transforming, and reporting, and build scalable solutions.
A day in the life
Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
About the team
The Science Tooling And Research (STAR) team builds and runs simulation experiments and delivers analyses that are central to understanding the performance of the entire AR system. This includes operational and software scaling characteristics, bottlenecks, and robustness to “chaos monkey” stresses -- we inform critical engineering and business decisions about Amazon’s approach to robotic system. We are seeking a Data Engineer to automate the pipeline and tools we support for generating data insights. As a Data Engineer, you will be responsible for the design and development of the data, metrics and reporting platforms for our team. You will implement new and automated data solutions, including big data capabilities, that support our scientists, analysts, and engineers, with large-scale data for training machine learning models, enabling metrics to evaluate their worthiness, while satisfying scalability, reliability, accuracy, performance and budget goals and driving automation and operational efficiencies.
Basic Qualifications
- 1+ years of data engineering experience
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Big Data Computer Science Data pipelines Data visualization DDL Distributed Systems Engineering ETL Hadoop HiveQL Informatica Machine Learning ML models NoSQL Oracle Pipelines Python Redshift Research Robotics Scala Spark SQL SSIS Statistics
Perks/benefits: Career development Health care Medical leave Parental leave
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