Big Data Analyst

Vantor Inc.
Herndon, VA, United States
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$122,000.0 - $160,000.0
Working hours
Regular working hours
Job source

Tech stack

Computer-Aided Design Artificial Intelligence Amazon Web Services Microsoft Azure Big Data Computer Programming Extract Transform Load (ETL) Data Security Data Visualization Data Warehousing Apache Hadoop Python (Programming Language)
+7 more
Machine Learning Power BI SQL Databases Data Streaming Tableau (Software) Apache Spark Apache Kafka

Job description

Vantor seeks a Big Data Analyst to join our Data Science & AI team supporting Defense & Aerospace clients. You will design scalable data pipelines, integrate diverse mission datasets, and enable advanced analytics and AI for critical programs. Responsibilities include building secure ETL workflows, optimizing big data platforms (e.g., Hadoop/Spark), and collaborating with AI engineers to productionize models. You’ll develop dashboards and visualizations that drive operational decisions. At Vantor, you’ll work in a culture of innovation, diversity, and continuous learning with competitive pay, bonus eligibility, and comprehensive benefits., * Design and maintain big data pipelines for defense and aerospace programs

  • Develop scalable data models and AI-ready datasets for mission analytics
  • Implement secure data ingestion, ETL, and real-time streaming solutions
  • Collaborate with AI engineers and data scientists to operationalize ML models
  • Optimize performance and reliability of large-scale data platforms
  • Ensure data security, governance, and compliance with defense standards
  • Build dashboards and reports to deliver actionable insights to stakeholders
  • Mentor junior team members and contribute to best practices and standards

Requirements

  • Big data technologies (Hadoop/Spark)
  • SQL and No
  • SQL databases
  • Python or Scala programming
  • Machine learning fundamentals
  • Data warehousing and ETLCloud platforms (AWS/Azure/GCP)
  • Data visualization (Tableau/Power BI)
  • Streaming data (Kafka/Kinesis)
  • Data security and governance
  • Statistics and experimental design

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