Posted 4w ago

Data Engineer

@ KDA Consulting
Herndon, Virginia, United States
OnsiteFull Time
Responsibilities:Design pipelines, Build workflows, Collaborate stakeholders
Requirements Summary:Active TS/SCI with polygraph; bachelor's in CS/engineering; experience in data engineering, AWS data services, SQL, Python; large-scale data and analytics.
Technical Tools Mentioned:AWS, SQL, Python, S3, Glue, Redshift, Lambda, EMR, Kinesis
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Job Description

KDA Consulting Inc. is seeking a highly skilled Data Engineer to design, build, and maintain scalable data pipelines and architectures supporting mission-critical programs within the Intelligence Community (IC). This role focuses on enabling efficient data processing, analytics, and decision-making by delivering reliable, high-quality data solutions in cloud environments.

The ideal candidate will have strong experience with AWS cloud services, data engineering best practices, and big data technologies, with the ability to operate in a fast-paced, collaborative environment supporting complex mission systems.

Data Pipeline Development & Engineering

  • Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources
  • Build and optimize data workflows supporting both batch and real-time processing
  • Ensure high availability and reliability of data pipelines across enterprise systems

AWS Cloud & Data Services

  • Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions
  • Design and manage cloud-based data architectures that are secure, scalable, and cost-efficient
  • Implement best practices for data storage, partitioning, and lifecycle management

Data Optimization & Performance

  • Optimize data storage and retrieval for performance, scalability, and cost efficiency
  • Implement indexing, partitioning, and query optimization strategies
  • Monitor and troubleshoot data pipeline performance issues

Data Quality & Governance

  • Ensure data accuracy, consistency, and integrity across all data pipelines and systems
  • Implement validation, monitoring, and error-handling mechanisms
  • Support data governance practices and compliance with security and IC standards

Collaboration & Integration

  • Work closely with data scientists, software engineers, and mission stakeholders to support analytics and operational needs
  • Integrate data solutions with enterprise applications, APIs, and downstream analytics platforms
  • Participate in Agile development processes and contribute to continuous improvement efforts