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1392- Data Engineer

Northern, Virginia


Alexandria, Arlington, McLean, Herndon, Chantilly, Washington DC

Support the configuration and ingestion of designated structured, unstructured, and semi-structured data repositories into capabilities that satisfy mission partner requirements and support a data analytics and DevOps pipeline to drive the client's rapid delivery of functionality. Maintain all operational aspects of data transfers, accounting for the security posture of the underlying infrastructure and the systems and applications supported and monitor the health of the environment through a variety of health tracking capabilities. Automate configuration management, leveraging tools, including NiFi, and stay current on data extract, transfer, and load (ETL) technologies and services. Work under
general guidance, demonstrate an initiative to develop approaches to solutions independently, review architecture, and identify areas for automation, optimization, right-sizing, and cost reduction to support the environment's overall health. Apply specialized knowledge of data engineering-specific technologies and services, leverage expertise in
databases and various approaches to structuring and retrieving of data, comprehend Cloud architectural constructs, and support the establishment and maintenance of Cloud environments programmatically using vendor consoles. Engage with multiple functional groups to comprehend client challenges, prototype new ideas and new technologies, help to create solutions to drive the next wave of innovation, and design, implement, schedule, test, and deploy full
features and components of solutions.


  • 2+ years of experience with machine learning, data science, or data engineering
  • Experience with the design, implementation and ETL process for databases
  • Experience with creating data pipelines
  • Experience with building machine learning models and predictive analytics
  • Experience with common programming languages, including SQL, Python, or R
  • Ability to articulate workflows and explain technical concepts to non-technical audiences
  • Ability to interact with multidisciplinary teams including data scientists and technical consultants in project- based areas
  • BA or BS degree


  • Experience with Big Data technologies, including HDFS, Impala, AWS, Glue, Azure, Cloudera, Hadoop, or Spark
  • Experience with data science frameworks including DataBricks, Data Robot, or Cloudera
  • Experience with distributed computing and optimizing pipelines
  • Experience with parsing a variety of data sources including Oracle, XML, JSON, or parquet
  • Experience with data visualization development and role of data integration


  • Secret