Data Scientist

BT-478 – Data Scientist
Location: Chantilly

**Please do NOT apply if you do not have an active Poly clearance. Those without a Poly will not be considered.**

Support Customer with the requirements for new system capabilities, the extension and maintenance of bulk data pipeline and enhancements for multiple applications in the customers' cloud computing environment.

Requirements

• 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 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 ETL’ing 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.

Optional Skills

• Demonstrated experience deploying capabilities on the Databricks unified analytics platform.
• Demonstrated experience with Elastic Map Reduce to run big data workloads.
• 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).