100% Remote Data Engineer

Job ID: 200
Location: Richmond VA

Summit Human Capital is seeking a highly motivated 100% REMOTE Data Engineer to support a Fortune 500 Company. This is a 12-month+ contract with long-term potential. This person will have the opportunity to design and test ETL solutions supporting crucial business units. The ideal candidate will meet the following criteria:


• In-depth experience with data warehousing (i.e. Dimensional Modeling, ETL) and relational database systems management concepts • 5 years of experience working with ETL tools including Talend, Informatica, or Data Stage • 5 years of experience with SQL, Stored Procedures and Table Design • 5 years of experience with SQL Query optimization and ETL Data loading Performance • 2 years of experience with shell scripting


• Data Engineering experience with Hadoop Platforms using HIVE, KAFKA, NiFi, and/or Spark • Experience using real time streaming technologies • Experience creating machine learning models and automating processes in production • Experience with cloud technologies (AWS, Azure, GCP)


• Design reliable ETL solutions supporting critical business processes across the business • Verify data solutions are compliant with enterprise security standards • Develop and perform tests, validate data flows, and create ETL processes to meet business requirements, including designing complex end-to-end solutions using BI platforms • Collaborate with analysts and developers to ensure jobs designed and developed meet minimum support standards before migration into the production environment • Partner with various infrastructure and application teams to develop process designs and complex transformations of data elements for the business • Uses strategies including indexing and partitioning to polish the data warehouse and big data environments, allowing improvement of the query response time and scalability • Define metadata and rules associated with ETL processes • Assist production support team in providing resolutions to production job failures and data issues

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