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Black Canyon Consulting

Data Engineer

Bethesda, MDmidAdded today

About this role

Black Canyon Consulting seeks a Data Engineer to design and maintain scalable data infrastructure supporting AI, machine learning, and analytics workloads. You'll build and optimize ETL/ELT pipelines, manage data platforms, and ensure data reliability across the full lifecycle from ingestion through deployment.

What you'll do

  • Design, implement, and maintain scalable data pipelines for analytical and AI/ML workloads
  • Build, monitor, and optimize ETL/ELT data transformation workflows
  • Integrate and configure databases, data lakes, data warehouses, and feature stores
  • Develop APIs and service layers exposing data or model endpoints to downstream systems
  • Implement data validation, quality controls, and reliability processes
  • Collaborate with data scientists, engineers, and analysts to support evolving data requirements

What they're looking for

  • Data pipeline design and development
  • ETL/ELT workflow optimization
  • Relational and non-relational databases
  • Data transformation and feature engineering
  • Cloud-based data platforms
  • API development and integration
  • Data modeling and architecture principles
  • Pipeline monitoring and troubleshooting

Benefits

  • Medical, dental, and vision coverage
  • 401k plan with employer contribution
  • Paid holidays and vacation
  • Tuition reimbursement
  • Competitive benefits package
  • Professional service and technology-focused environment
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Black Canyon Consulting

Black Canyon Consulting provides security, infrastructure, and modernization services for high-traffic biomedical research platforms, particularly supporting the National Center for Biotechnology Information (NCBI) at the National Institutes of Health. The company is hiring for security engineers, DevSecOps specialists, full-stack developers, QA engineers, and platform engineers to build resilient, compliant systems serving millions of users across hybrid cloud and on-premises environments.

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Likely interview questions

  • Walk us through a complex data pipeline you designed—what challenges did you face and how did you optimize it?
  • Describe your experience choosing between ETL and ELT approaches for different use cases.
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