Data Engineer

Artech LLC

  • Chicago, IL
  • 30+ days ago
  • $65–$70 Per Hour
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Skills

  • Amazon Web Services (AWS)unmatched
  • Apache Sparkunmatched
  • Cloud Applicationsunmatched
  • Cloud Computingunmatched
  • Computer Programmingunmatched
  • Computer Securityunmatched
  • Continuous Deployment/Deliveryunmatched
  • Continuous Integrationunmatched
  • Cross-Functionalunmatched
  • Customer Experienceunmatched
  • Data Modelingunmatched
  • Data Processingunmatched
  • Data Scienceunmatched
  • Debugging Skillsunmatched
  • DevOpsunmatched
  • Jenkinsunmatched
  • Machine Learningunmatched
  • Performance Tuning/Optimizationunmatched
  • Python Programming/Scripting Languageunmatched
  • Scalable System Developmentunmatched
  • Security Complianceunmatched
  • Software Engineeringunmatched
  • Systems Reliabilityunmatched
  • Systems Scalabilityunmatched

Description

Job Title: Data Engineer
Location: McLean, VA (Onsite/Hybrid – Local candidates preferred)
Duration: 9 Months Contract

 

We are seeking a highly skilled MLOps Engineer / Python Developer with strong experience in building and maintaining scalable data and machine learning pipelines. The ideal candidate will have hands-on expertise in Python, AWS, Kubernetes, and ML workflow tools (Kubeflow) along with solid experience in data processing frameworks like Spark and Pandas.

Required Skills & Qualifications

  • Strong programming experience in Python
  • Hands-on experience with AWS (or similar cloud platforms)
  • Expertise in Kubernetes and Kubeflow (or similar orchestration/workflow tools)
  • Experience with Spark, Pandas, NumPy for data processing
  • Must have previous client experience working for this customer in the past 5 years

Preferred Skills & Qualifications

  • Solid understanding of MLOps, ML lifecycle, and feature engineering
  • Familiarity with CI/CD tools (Jenkins or similar)
  • Experience in debugging, performance tuning, and vulnerability remediation

Day-to-Day Responsibilities

  • Develop, maintain, and optimize data and model-serving pipelines using Kubeflow and Spark
  • Implement feature engineering workflows for machine learning models
  • Deploy, test, and monitor ML applications in cloud environments
  • Collaborate with Data Scientists and cross-functional teams to productionize models
  • Identify and fix bugs, vulnerabilities, and performance issues
  • Handle feature requests and enhancements for existing systems
  • Support and manage CI/CD pipelines and DevOps processes
  • Ensure system scalability, reliability, and security compliance

Company Benefits & Culture

  • Comprehensive health, dental, and vision insurance
  • 401(k) with company match
  • Opportunities for professional development and growth

 

Numbers & Facts

LocationChicago, IL
Salary$65–$70 Per Hour

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