Data Scientist

Bespoke Technologies; Chantilly (VA); Presencial; USD 110 000 - 160 000; Tempo integral

Resumo da oferta

Bespoke Technologies in Chantilly, VA is seeking a Data Scientist with an active Poly clearance. You will support customers by defining system capabilities and extending bulk data pipelines across their cloud environments.

You will transform and analyze large data sets, build dashboards, and work with stakeholders in an Agile setting to deliver measurable business insights. Eligibility for government-cleared roles is required.

Qualificações

• Experience with big data processing using Spark, PySpark and Python.
• Experience data mapping, extraction, transformation, loading (ETL).
• Experience building analytic reports in CloudWatch and Kibana.
• Experience converting OS/data logs into reports and dashboards.
• Experience with RegEx, SQL/MySQL/PostgreSQL, and XML/JSON.
• Experience with notebooks and data modeling in Visual Studio.
• Experience ETL’ing disparate data into indexed, query-friendly structures.
• Experience data quality analysis and ETL design documentation.
• Experience interfacing with customers and agile development.

Responsabilidades

• Support customer with requirements for new system capabilities and data pipelines.
• Extend and maintain bulk data pipelines across customer cloud environments.

Conhecimentos

Spark/PySpark/Python

ETL

Data mapping/extraction/loading

CloudWatch/Kibana dashboards

RegEx

SQL/MySQL/PostgreSQL

XML/JSON data formats

Notebooks/Visual Studio (IDE)

Data quality analysis

ETL design documentation (data mapping

Customer/partner interfacing

Agile development support

Ferramentas

Databricks

Elastic/ELK stack

Elastic Map Reduce (EMR)

Cloud services (Lambda, SQS, EC2)

Power BI/Kibana/CloudWatch

Descrição da oferta de emprego

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).