Job Requirements
Washington Dc Brm, DC Tampa, FL Fayetteville, NC
Secret Polygraph not specified
Career Level not specified
$120,000 - $185,000
Job Description
Data Engineer (Junior & Senior Openings)
Overview
We are seeking Data Engineers at both junior and senior levels to support a growing portfolio of data and analytics initiatives within complex, mission-driven environments. This role centers on designing and building scalable data solutions that support advanced analytics, reporting, and decision-making across large and diverse datasets.
This position is part of a centralized data engineering and analytics function, partnering closely with data platform teams, analysts, and software engineers to develop modern data pipelines, analytics workflows, and enterprise data environments. The work involves leveraging distributed processing frameworks, cloud-based data platforms, and visualization tools to deliver actionable insights.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python, PySpark, SQL, or R
Ingest, process, and transform structured and unstructured data from multiple data sources
Build and maintain analytics-ready datasets to support reporting, dashboards, and data visualization tools (Power BI, Tableau, Qlik)
Develop and optimize ETL/ELT workflows and data processing jobs within distributed environments
Work with large-scale datasets using big data technologies such as Spark and related frameworks
Partner with cross-functional teams (engineering, analytics, and business stakeholders) to deliver data-driven solutions
Translate business or mission needs into technical data solutions and scalable architectures
Implement data quality checks, validation processes, and transformation logic to ensure data integrity
Support deployment and integration of enterprise data platforms and analytics environments
Troubleshoot and resolve issues across pipelines, ingestion processes, and processing layers
Participate in Agile development practices, including sprint planning, design discussions, and iterative delivery
Required Technical Skills
Hands-on experience with Python and SQL for data processing and analysis
Experience with PySpark or other distributed data processing frameworks
Familiarity with R (or willingness to work with statistical/analytical languages)
Experience building and maintaining data pipelines (ETL/ELT) and workflow automation
Experience working with large datasets and understanding distributed data processing concepts
Exposure to or experience with data visualization tools such as Power BI, Tableau, or Qlik
Strong understanding of data modeling, data transformation, and data architecture fundamentals
Ability to work effectively in a collaborative, cross-functional team environment
Preferred / Nice-to-Have Skills
Experience with big data ecosystem tools such as Hive, Hadoop, or Spark-based platforms
Hands-on experience with Databricks, AWS EMR, or similar cloud-based data platforms
Exposure to Palantir Foundry or similar enterprise analytics/data integration platforms
Experience supporting analytics, reporting, or machine learning workflows
Familiarity with cloud environments and modern data platform architectures
Experience working in large-scale, enterprise, or regulated environments
Experience Levels
Junior Level
Early-career experience in data engineering, analytics, or software development
Exposure to data pipelines, data processing tools, or reporting/visualization platforms
Ability to contribute to development tasks and collaborate within a team environment
Senior Level
Proven experience designing, building, and maintaining enterprise-scale data solutions
Strong background developing and optimizing data pipelines using Python/PySpark and SQL
Experience supporting analytics platforms and data visualization/reporting ecosystems
Ability to influence architecture decisions and mentor junior team members
Strong capability translating complex requirements into scalable, efficient solutions
Additional Details
Multiple openings available supporting several high-priority programs
Work spans a variety of project areas and data initiatives (not tied to a single program)
Hybrid work environment with regular on-site collaboration
Limited travel may be required depending on project alignment
Opportunity for continued training and hands-on experience with modern data tools and platforms
Clearance Requirement
Active clearance required (minimum Secret; TS or TS/SCI preferred)
Overview
We are seeking Data Engineers at both junior and senior levels to support a growing portfolio of data and analytics initiatives within complex, mission-driven environments. This role centers on designing and building scalable data solutions that support advanced analytics, reporting, and decision-making across large and diverse datasets.
This position is part of a centralized data engineering and analytics function, partnering closely with data platform teams, analysts, and software engineers to develop modern data pipelines, analytics workflows, and enterprise data environments. The work involves leveraging distributed processing frameworks, cloud-based data platforms, and visualization tools to deliver actionable insights.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python, PySpark, SQL, or R
Ingest, process, and transform structured and unstructured data from multiple data sources
Build and maintain analytics-ready datasets to support reporting, dashboards, and data visualization tools (Power BI, Tableau, Qlik)
Develop and optimize ETL/ELT workflows and data processing jobs within distributed environments
Work with large-scale datasets using big data technologies such as Spark and related frameworks
Partner with cross-functional teams (engineering, analytics, and business stakeholders) to deliver data-driven solutions
Translate business or mission needs into technical data solutions and scalable architectures
Implement data quality checks, validation processes, and transformation logic to ensure data integrity
Support deployment and integration of enterprise data platforms and analytics environments
Troubleshoot and resolve issues across pipelines, ingestion processes, and processing layers
Participate in Agile development practices, including sprint planning, design discussions, and iterative delivery
Required Technical Skills
Hands-on experience with Python and SQL for data processing and analysis
Experience with PySpark or other distributed data processing frameworks
Familiarity with R (or willingness to work with statistical/analytical languages)
Experience building and maintaining data pipelines (ETL/ELT) and workflow automation
Experience working with large datasets and understanding distributed data processing concepts
Exposure to or experience with data visualization tools such as Power BI, Tableau, or Qlik
Strong understanding of data modeling, data transformation, and data architecture fundamentals
Ability to work effectively in a collaborative, cross-functional team environment
Preferred / Nice-to-Have Skills
Experience with big data ecosystem tools such as Hive, Hadoop, or Spark-based platforms
Hands-on experience with Databricks, AWS EMR, or similar cloud-based data platforms
Exposure to Palantir Foundry or similar enterprise analytics/data integration platforms
Experience supporting analytics, reporting, or machine learning workflows
Familiarity with cloud environments and modern data platform architectures
Experience working in large-scale, enterprise, or regulated environments
Experience Levels
Junior Level
Early-career experience in data engineering, analytics, or software development
Exposure to data pipelines, data processing tools, or reporting/visualization platforms
Ability to contribute to development tasks and collaborate within a team environment
Senior Level
Proven experience designing, building, and maintaining enterprise-scale data solutions
Strong background developing and optimizing data pipelines using Python/PySpark and SQL
Experience supporting analytics platforms and data visualization/reporting ecosystems
Ability to influence architecture decisions and mentor junior team members
Strong capability translating complex requirements into scalable, efficient solutions
Additional Details
Multiple openings available supporting several high-priority programs
Work spans a variety of project areas and data initiatives (not tied to a single program)
Hybrid work environment with regular on-site collaboration
Limited travel may be required depending on project alignment
Opportunity for continued training and hands-on experience with modern data tools and platforms
Clearance Requirement
Active clearance required (minimum Secret; TS or TS/SCI preferred)
group id: kforcecx
We offer roles across all three clearance levels: Confidential, Secret and Top Secret. With a Top Secret Facilities clearance, a proven subcontractor track record and a deep understanding of agencies across Defense, Intelligence, Homeland, Justice and Federal Civilian Sectors, Kforce brings more than 20 years of experience to supporting critical missions at federal, state and local levels.
