WorldWide Amazon Stores FinTech (WWASFT) team is looking for a Data Engineer who is datadriven uncompromisingly detail oriented smart efficient and driven to help our business succeed. You have passion for technology. You are keen to leverage existing skills while trying new approaches. You are not toolcentric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your nontechnical customers in simple terms.
As a Data Engineer you will be working in one of the worlds largest and most complex data warehouse environments. You will design implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources aggregate and retrieve data in a fast and safe mode curate data that can be used in reporting analysis machine learning models and adhoc data requests. You will be exposed to cutting edge AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and Tech leaders to gather infrastructure requirements design data infrastructure build up data pipelines and datasets to meet business needs. You stay abreast of emerging technologies investigating and implementing where appropriate
Key job responsibilities
Design and develop the pipelines required for optimal extraction transformation and loading of data from a wide variety of data sources using SQL Python and AWS big data technologies.
Oversee and continually improve production operations including optimizing data delivery redesigning infrastructure for greater scalability code deployments bug fixes and overall release management and coordination.
Establish and maintain best practices for the design development and support of data integration solutions including documentation.
Work closely with Product teams Data Scientists Software developers and Business Intelligence Engineer to explore new data sources and deliver the data.
Able to read write and debug data processing and orchestration code written Python/Scala etc following best coding standards (e.g. version controlled code reviewed etc.
1 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)
Knowledge of writing and optimizing SQL queries in a business environment with largescale complex datasets
Experience with big data technologies such as: Hadoop Hive Spark EMR
Experience with any ETL tool like Informatica ODI SSIS BODI Datastage etc.
Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions
Experience with nonrelational databases / data stores (object storage document or keyvalue stores graph databases columnfamily databases)
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91200/year in our lowest geographic market up to $185000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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 This position will remain posted until filled. Applicants should apply via our internal or external career site.