Data Scientist - Active TS/SCI with FSP

Tomorrow Hire Llc.; Chantilly (VA); Presencial; USD 230 000 - 250 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health insurance

401(k) retirement plan

Paid time off

Bonuses

Resumo da oferta

Tomorrow Hire Llc. is seeking a Data Scientist to support a mission-critical Sponsor environment in Chantilly, VA. You will build scalable data pipelines, perform quality analysis, and transform logs into actionable metrics using Spark, PySpark, Python, and SQL.

The role emphasizes ETL development, data stewardship, and collaboration with customers and partners to meet technical objectives, while adhering to Agile practices and on-site requirements.

Qualificações

• Hands-on experience with Spark, PySpark, and Python for big data processing.
• Experience with ETL design and data mapping across sources.
• Analytic reporting using CloudWatch and Kibana.
• Transforming OS logs into dashboards and reports.
• Strong SQL, MySQL, PostgreSQL and XML/JSON data handling.
• Experience interfacing with customers and partners; Agile support.
• Active TS/SCI with Full Scope Polygraph required at application.

Responsabilidades

• Design and maintain data processing and ETL workflows for diverse datasets.
• Map, extract, transform, load, standardize, and validate data sources.
• Leverage Spark, PySpark, Python to process large datasets.
• Convert logs into analytics reports, metrics, and dashboards.
• Create analytic reports using CloudWatch and Kibana.
• Develop ETL documentation including source-to-target mappings.
• Process XML and JSON data with RegEx as needed.
• Work with SQL databases; use notebooks/Visual Studio for modeling.
• Collaborate with customers and partners to define technical goals.
• Support Agile development; contribute to task scope and reviews.

Conhecimentos

Spark

PySpark

Python

SQL

ETL processes

Kibana

CloudWatch

RegEx

Data quality

Data modeling

Formação académica

Bachelor's degree in a relevant field

Ferramentas

Elasticsearch

Logstash

Kibana

ETL tooling

SQL databases

Python IDEs/notebooks

Descrição da oferta de emprego

Location: Chantilly, VA
Clearance Required: TS/SCI with Full Scope Polygraph (FSP)
Position Type: Full-Time, On-Site, Salary : $230,000-$250,000/yr.

We are seeking a Data Scientist to support a mission-critical Sponsor environment focused on processing, transforming, analyzing, and managing complex datasets from structured and unstructured sources. This role will develop and maintain scalable data processing pipelines, perform data quality analysis, transform system and event logs into actionable reports and metrics, and support cloud-based analytics capabilities.

The ideal candidate will have strong hands‑on experience with Spark, PySpark, Python, SQL, ETL processes, and big data technologies , along with experience developing analytic reports and working directly with customers and integration partners to understand technical objectives.

Primary Responsibilities:

• Design, develop, and maintain data processing and ETL workflows for structured and unstructured datasets.
• Perform data mapping, extraction, transformation, loading, standardization, and validation across multiple data sources.
• Use big data processing technologies such as Spark, PySpark, and Python to process and analyze complex datasets.
• Process and convert operating system, system, event, and data logs into analytic reports, metrics, and dashboards.
• Develop analytic reports using tools such as CloudWatch and Kibana .
• Perform extensive data review and data quality analysis to identify inconsistencies and ensure data integrity.
• Develop ETL design documentation, including source-to-target mappings and data dictionary information.
• Process data file formats including XML and JSON and use Regular Expressions (RegEx) as required for data extraction and transformation.
• Work with relational database technologies including SQL, MySQL, and PostgreSQL .
• Use IDEs, notebooks, and tools such as Visual Studio for data modeling, development, and analysis.
• Develop enriched, query-friendly structured datasets from disparate structured and unstructured data formats.
• Interface directly with customers and integration partners to gather, clarify, and translate detailed objectives into technical solutions.
• Support Agile development activities by contributing to task definition, scope development, and reviews.
• Develop and maintain processing pipelines, technical workflows, software standards, and supporting documentation.
• Assist with identifying, classifying, validating, and processing incoming datasets, including non-standard data formats.
• Develop scripts and software modules as needed to triage and transform datasets into standardized data models.
• Support deployment of data processing pipelines to cloud analytics platforms.

Minimum Qualifications:

• Demonstrated experience with big data processing technologies including Spark, PySpark, and Python
• Demonstrated experience with data mapping, extraction, transformation, and loading (ETL)
• Experience developing analytic reports using tools such as CloudWatch and Kibana
• Experience processing and converting operating system and data logs into reports, metrics, and dashboards
• Experience using Regular Expressions (RegEx)
• Experience with SQL, MySQL, and PostgreSQL
• Experience processing XML and JSON data formats
• Experience with IDEs and data modeling through notebooks and Visual Studio
• Experience transforming disparate structured and unstructured data into enriched, query-friendly structured datasets
• Experience performing extensive data review and data quality analysis
• Experience developing ETL design documentation , including source-to-target mapping and data dictionary information
• Experience interfacing with customers and integration partners to gather and clarify detailed objectives
• Experience supporting Agile development , including task definition, scoping, and review
• Active TS/SCI clearance with Full Scope Polygraph (FSP) required at the time of application
• Ability to work full-time on-site in Chantilly, VA

Preferred Qualifications:

• Experience deploying capabilities using the Databricks unified analytics platform
• Experience with Elastic MapReduce (EMR) for big data workloads
• Experience joining multiple complex datasets using Spark
• Experience tuning Spark streaming and batch jobs for cluster utilization and performance
• Experience deploying complex, notebook-based pipelines
• Experience with Python data analysis libraries such as Pandas
• Experience with cloud services such as Lambda, SNS/SQS, and EC2
• Experience with DevOps and cloud technologies including CloudWatch, Lambda, SQS, DynamoDB, and RDS
• Experience with Elastic, Elasticsearch, Logstash, and Kibana (ELK stack)
• Experience evaluating, formatting, standardizing, and maintaining data from multiple sources
• Experience developing and managing data processing workflows within customer pipelines
• Experience evaluating, extracting, and processing system and event logs
• Experience identifying and implementing COTS and open-source data enhancement capabilities
• Experience developing and deploying processing pipelines to cloud analytics platforms
• Experience developing software standards, practices, and technical documentation

Additional Requirements:

• Ability to work core hours of 9:00 AM-3:00 PM
• Ability to provide occasional weekend or after-hours support for operational issues, deployments, and critical activities
• Strong ability to work with customers, integration partners, and technical teams in a collaborative environment

Benefits

Salary: $230,000-$250,000/yr. based on experience.

Our client offers a comprehensive and competitive benefits package, including:

• 100% Company-Paid Health Insurance: Full coverage for medical, dental, and vision insurance for employees and their dependents (United Healthcare and Guardian).
• Protection Plans: Employer-paid life, short-term disability, and long-term disability insurance.
• 401(k) Retirement Contribution: 15% of base salary contributed by the company, fully vested from day one.
• Paid Time Off: 200 hours of PTO annually (accrued), in addition to 11 federal holidays.
• Bonuses: Recruitment and business development bonus opportunities based on performance and company growth.