Address
Form of work
Salary- 2+ years of Data Engineering experience
- 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)
Our team of high caliber software developers, data scientists, statisticians and product managers use rigorous quantitative approaches to ensure that we target the right product to the right customer at the right moment, managing tradeoffs between click through rate, approval rates and lifetime value. In order to accomplish this we leverage the wealth of Amazon’s information to build a wide range of probabilistic models, set up experiments that ensure that we are thriving to reach global optimums and leverage Amazon’s technological infrastructure to display the right offerings in real time.
As a Data Engineer you will be working in one of the world's largest and most complex data warehouse environments. You should be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets. You will build data analytical solutions that will address increasingly complex business questions.
You should be expert at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive. You will be working on developing solutions that provide some of the unique challenges of space, size and speed. You will implement data analytics using cutting edge analytics patterns and technologies that are inclusive of but not limited to various AWS Offerings - EMR, Lambda, Kinesis, and Spectrum. You will extract huge volumes of structured and unstructured data from various sources (Relational /Non-relational/No-SQL database) and message streams and construct complex analyses. You will write scalable code and tune performance running over billion of rows of data. You will implement data flow solutions that process data on Spark, Redshift and store in both Redshift and File based storage (S3) for reporting and adhoc analysis.
You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion.
You should have excellent business and 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. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $81,000/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
