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Form of workJob Description
Looking for that ENTRY LEVEL opportunity to jumpstart your Data Engineer career?!
Our customer is hiring for a Data Engineer , this position sits out of Ft Liberty, NC. You must have a Top Secret clearance already and a Bachelors degree in a STEM field.
**PLEASE DO NOT APPLY IF YOU DONT HAVE AN ACTIVE TOP SECRET CLEARANCE ***
TS Clearance Required
• Minimum of 2 years experience in the field
• Bachelor’s degree in a STEM field with preference towards Computer Science and Software Engineering.
• Verifiable work experience working with data structures, database management, distributed computing, and API driven architectures using SQL and No-SQL engines.
• A Certified Data Management Professional certification is preferred.
• Proficient in modeling frameworks like Universal Modeling Language (UML), Agile Development, and Git Operations.
The Data Engineer shall perform the following tasks:
• Developing, maintaining, and testing infrastructures for data generation to transform data from various structured and unstructured data sources.
• Develop complex queries to ensure accessibility while optimizing the performance of NoSQL and or big data infrastructure. Create and maintain optimal data pipeline architecture.
• Build and maintain the infrastructure to support extraction, transformation, and loading (ETL) of data from a wide variety of data sources. Extract data from multiple data sources, relational SQL and NoSQL databases, and other platform APIs, for data ingestion and integration.
• Configure and manage data analytic frameworks and pipelines using databases and tools such as NoSQL, SQL, HDInsight, MongoDB, Cassandra, Neo4j, GraphDB, OrientDB, Spark, Hadoop, Kafka, Hive, and Pig.
• Apply distributed systems concepts and principles such as consistency and availability, liveness and safety, durability, reliability, fault-tolerance, consensus algorithms.
• Administrate cloud computing and CI/CD pipelines to include Azure, Google, and Amazon Web Service (AWS).
• Coordinate with stakeholders, including product, data and design teams to assist with data-related technical issues and support their data infrastructure needs
