Data Scientist

Bespoke Technologies, Inc.; Chantilly (VA); On-site; USD 120,000 - 150,000; Full time

Job summary

Bespoke Technologies, Inc. in Chantilly seeks a Data Scientist to support customer requirements, extend and maintain bulk data pipelines, and enhance analytics across multiple cloud-based applications.

The role focuses on building scalable data flows, processing logs, and delivering dashboards and reports for stakeholders. Ideal candidates have hands-on experience with Spark, PySpark, Python, SQL and ETL, plus exposure to analytics tools like CloudWatch and Kibana.

Qualifications

• Experience with big data processing using Spark, PySpark and Python.
• Experience in data mapping, extraction, transformation, and loading.
• Experience building analytic reports in CloudWatch and Kibana.
• Experience converting OS and data logs into reports and dashboards.
• Familiar with regex for text extraction and pattern matching.
• Proficient with SQL databases (MySQL/PostgreSQL).
• Experience processing XML/JSON data formats.
• Experience with notebooks and data modeling in IDEs like Visual Studio.
• Experience ETL-ing disparate data into structured, indexed formats.
• Experience data quality analysis and documentation.

Responsibilities

• Support customer requirements for new system capabilities.
• Extend and maintain bulk data pipelines across applications.
• Enhance data processing in the customer's cloud environment.
• Collaborate with stakeholders to clarify objectives and deliverables.
• Assist Agile teams with tasking definition and scope review.

Skills

Spark

PySpark

Python

SQL

ETL

Data mapping

Data quality analysis

Dashboards/Reports

Regex

Tools

Databricks

Elastic Stack (ELK)

CloudWatch

Kibana

Notebooks

Visual Studio

Job description

BT-478 - Data Scientist

Location: Chantilly

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).