Systems Engineer

1 month ago


McLean, United States Integrated Intel Solutions Full time
Job DescriptionJob Description

Systems Engineer


Summary

The Sponsor is seeking support for the migration of legacy data, development of new capabilities, and extension and maintenance of bulk data pipeline


Job Description

The Sponsor is seeking support for the DevOps operations that include migration of legacy data, development of new system capabilities, extension and maintenance of bulk data pipeline and enhancements for multiple mission applications in the Sponsors cloud computing environment. The core hours for all positions not otherwise identified shall be 9:00AM 3:00PM. Weekend or after-hours support may be required for operational issues, deployments and critical activities. The Systems Engineer will evaluate, format and maintain data from multiple sources; develop and manage data processing workflows in customer pipeline; and evaluate, extract and process System and Event Logs. They will develop and maintain processing pipelines and documentation; assist with identifying, classifying, and verifying incoming dataset types; and identify and implement COTS and Open Source Data Enhancement capabilities. The Systems Engineer will also code scripts and software modules as needed basis to triage and convert datasets that arrive in non-standard formats to fit a de-normalized row and column data model. They will store, standardize, extract, reference, and validate data; develop and deploy processing pipelines to cloud analytics platforms; and develop requirements to support data analytics customers and integration partners. They will develop software standards and practices documentation and support Agile development.


Mandatory Technologies/Tools

  • Demonstrated experience utilizing big data processing tech such as Spark, Pyspark, and Python.
  • Demonstrated experience data mapping, extraction, transformation and loading.
  • Demonstrated experience building analytic reports in tools such as CloudWatch and Kibana.
  • Demonstrated experience using AWS Step Functions to coordinate ETL pipelines
  • Demonstrated experience processing and converting of OS and Data Logs into reports and metrics Dashboards.
  • Demonstrated experience with Regular Expressions (RegEx).
  • Demonstrated experience with SQL, MySQL, PostgresSQL.
  • Demonstrated experience with Data file type processing XML, JSON.
  • Demonstrated experience with IDEs and Data Modeling through Notebooks and Visual Studio.
  • Demonstrated experience ETLing data from disparate structured & unstructured data formats into enriched, query-friendly structured data in indexed files.
  • Demonstrated experience performing extensive data review and data quality analysis.
  • Demonstrated experience developing ETL design documentation including source and target mapping and data dictionary information.
  • Demonstrated experience interfacing with customers and integration partners for gaining and clarifying detailed objectives.
  • Demonstrated experience supporting Agile development by contributing to tasking definition, scope and review.


Desired)

  • Demonstrated experience deploying capabilities on the Databricks unified analytics platform.
  • Demonstrated experience in optimizing Databricks Delta Tables for query, merge and stream operations.
  • Demonstrated experience with CI/CD using Jenkins.
  • Demonstrated experience in joining multiple complex data sets using Spark.
  • Demonstrated experience in tuning Spark streaming and batch jobs for cluster utilization and speed.
  • Demonstrated experience in deploying complex, notebook-based pipelines.
  • Demonstrated experience in Python data analysis libraries such as Pandas.
  • Demonstrated experience utilizing Cloud services such as Lambda, SNS/SQS, or EC2.
  • Demonstrated experience with DevOps tools to include Cloudwatch, Lambda, SQS, Dynamo and RDS.
  • Demonstrated experience working with Elastic, ElasticSearch/Logstash/Kibana (ELK stack).



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