Amazon
Data Engineer , Devices Sales & Marketing
Amazon, Seattle, Washington, us, 98127
Data Engineer, Devices Sales & Marketing Job ID: 2871119 | Amazon.com Services LLC
Apply fast, check the full description by scrolling below to find out the full requirements for this role. Do you want to build the premium shopping experiences for millions of Amazon customers? Do you want to work on performance challenges for providing the best recommendations in less than 200 milliseconds, given millions of customers and millions of products? Are you interested in working on delivering data to Machine Learning and data science, believing every customer should not have the same experience? Amazon has a role for you. As an Amazon.com Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments. You should be an expert in the architecture of DW solutions for the Enterprise using multiple technologies (RDBMS, Columnar, Cloud). You should excel in the design, creation, management, and business use of extremely large datasets. 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. Above all, you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change. Key Responsibilities
Architecture design and implementation of next generation data pipelines and BI solutions. Build and deliver high quality data architecture and pipelines to support business analyst, data scientists, and customer reporting needs. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers. A Day in the Life A Data Engineer works closely with business teams to identify opportunities and build efficient solutions using various platforms like Redshift, AWS, Spark, etc. They interface with business customers to gather requirements and build Data pipelines to drive key business decisions. Responsibilities include building scalable data pipelines and architecture while sourcing data from varied sources including APIs, File Systems, and RDBMS, and monitoring and troubleshooting operational issues in data pipelines. BASIC QUALIFICATIONS
1+ years of data engineering experience. Experience with data modeling, warehousing and building ETL pipelines. Experience with SQL. Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala). Experience with one or more scripting languages (e.g., Python, KornShell). Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model. 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. Knowledge of distributed systems as it pertains to data storage and computing. Knowledge of cloud services such as AWS or equivalent. 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. Our inclusive culture empowers Amazonians to deliver the best results for our customers. Posted:
November 13, 2024 (Updated about 13 hours ago)
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Apply fast, check the full description by scrolling below to find out the full requirements for this role. Do you want to build the premium shopping experiences for millions of Amazon customers? Do you want to work on performance challenges for providing the best recommendations in less than 200 milliseconds, given millions of customers and millions of products? Are you interested in working on delivering data to Machine Learning and data science, believing every customer should not have the same experience? Amazon has a role for you. As an Amazon.com Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments. You should be an expert in the architecture of DW solutions for the Enterprise using multiple technologies (RDBMS, Columnar, Cloud). You should excel in the design, creation, management, and business use of extremely large datasets. 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. Above all, you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change. Key Responsibilities
Architecture design and implementation of next generation data pipelines and BI solutions. Build and deliver high quality data architecture and pipelines to support business analyst, data scientists, and customer reporting needs. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers. A Day in the Life A Data Engineer works closely with business teams to identify opportunities and build efficient solutions using various platforms like Redshift, AWS, Spark, etc. They interface with business customers to gather requirements and build Data pipelines to drive key business decisions. Responsibilities include building scalable data pipelines and architecture while sourcing data from varied sources including APIs, File Systems, and RDBMS, and monitoring and troubleshooting operational issues in data pipelines. BASIC QUALIFICATIONS
1+ years of data engineering experience. Experience with data modeling, warehousing and building ETL pipelines. Experience with SQL. Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala). Experience with one or more scripting languages (e.g., Python, KornShell). Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model. 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. Knowledge of distributed systems as it pertains to data storage and computing. Knowledge of cloud services such as AWS or equivalent. 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. Our inclusive culture empowers Amazonians to deliver the best results for our customers. Posted:
November 13, 2024 (Updated about 13 hours ago)
#J-18808-Ljbffr