N3002 - Data Scientist; RV

Job Description Are you a high-performing Data Scientist driven to turn complex, multi-source intelligence data into actionable mission insights? Janus Soft is seeking a Senior Data Scientist & ETL Engineer to engineer robust big data pipelines, perform comprehensive data quality analysis, and design modern analytics dashboards across enterprise and cloud environments.

In this pivotal role, you will lead end-to-end data processing workflows using Python, PySpark, and Apache Spark. You will map, extract, transform, and load (ETL) disparate structured and unstructured datasets into enriched, query-friendly formats. Working in an Agile team environment, you will convert operating system and data logs into dynamic metrics dashboards using Cloud Watch and Kibana, develop complete ETL technical documentation and source-to-target data dictionaries, and interface directly with mission partners to refine analytic objectives.

If you excel at solving complex data puzzles and building scalable pipelines that empower decision-makers, Janus Soft provides the premier platform and backing to accelerate your career.

• Clearance:
  Active TS/SCI with Full Scope Polygraph (Strict Requirement).
• Big Data Processing:
  Extensive hands-on experience utilizing big data processing frameworks including Spark, PySpark, and Python .
• ETL & Data Engineering:
  Proven track record with data mapping, extraction, transformation, and loading (ETL) from disparate structured and unstructured formats into enriched, query-friendly, indexed data structures.
• Relational Databases & Querying:
  Advanced proficiency with SQL, MySQL, and PostgreSQL .
• Data Formats & Parsing:
  Demonstrated experience parsing and processing complex file types including XML, JSON , and using Regular Expressions (Reg Ex) .
• Log Processing & Dashboarding:
  Hands-on experience converting OS and data logs into custom reports and metrics dashboards using tools like Cloud Watch and Kibana .
• Data Analysis & Modeling Tools:
  Proficiency using IDEs and notebook environments (Visual Studio Code, Jupyter, Databricks notebooks) for data modeling and interactive analysis.
• Data Quality & Documentation:
  Strong experience conducting data quality analysis, data validation, and developing complete ETL design documentation, including source-to-target mappings and data dictionaries.
• Agile & Stakeholder
  
  Collaboration:
  
  Demonstrated experience interfacing with customers and integration partners to define scope and contributing actively to Agile sprint planning and execution.

• Demonstrated experience deploying analytics capabilities on the Databricks unified analytics platform and deploying notebook-based pipelines.
• Hands-on experience running and optimizing big data workloads on AWS Elastic Map Reduce (EMR) .
• Advanced expertise tuning Spark streaming and batch jobs for maximum cluster utilization, memory management, and processing speed.
• Proficiency with core Python data science libraries such as Pandas and Num Py .
• Direct experience leveraging AWS Cloud services including Lambda, SQS/SNS, EC2, DynamoDB, and RDS .
• In-depth working knowledge of the Elastic Stack (Elasticsearch, Logstash, Kibana - ELK) .