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Bachelors degree in computer science, engineering, mathematics, or a related technical discipline
Industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc) Experience working with AWS big data technologies (EMR, Redshift, S3, AWS Glue, Kinesis and Lambda for Serverless ETL) Knowledge of data management fundamentals and data storage principles Knowledge of distributed systems as it pertains to data storage and computing Hands-on experience and advanced knowledge of SQL Basic scripting skills using Python and Scala Basic understanding of Machine Learning Design and implement scalable data infrastructure supporting RCSs compliance and risk management initiatives Develop robust data pipelines and analytics processes that enable real-time decision making Collaborate with compliance officers, software engineers, and product managers to deliver reliable data solutions Lead technical initiatives and mentor team members in best practices for data engineering Create automated systems to replace manual processes and support Amazons global expansion 3+ years of data engineering experience Experience with SQL Experience with data modeling, warehousing and building ETL pipelines Experience with one or more query language (eg, SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Experience with one or more scripting language (eg, Python, KornShell) Experience with big data technologies such as: Hadoop, Hive, Spark, EMR Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc
Amazon
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