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Intertwine Associates

AI / Data Engineer – Mid-Level - Python, Azure Data & ML Pipelines

Data EngineeringUpdated on Nov 13
Full-time

About the Job

Requirements

  • At least 3 years of experience developing or supporting advanced statistical, machine learning, or data pipeline solutions.
  • Proficiency in Python, including Pandas.
  • Strong SQL skills and experience integrating relational database sources.
  • Hands-on experience with Azure cloud environments.
  • Experience with ETL development using Python and Microsoft technologies.
  • Experience with data validation, schema enforcement, and quality assurance.
  • Familiarity with open-source data processing libraries such as NumPy, scikit-learn, PyTorch, or TensorFlow.
  • Excellent written and verbal communication skills.
  • U.S. citizenship or lawful permanent residency may be required per contract.
  • Ability to obtain an agency Public Trust clearance.

Responsibilities

  • Develop production-grade ETL workflows using Python and Microsoft-based frameworks.
  • Ingest, transform, and validate structured and unstructured data.
  • Implement schema enforcement, data validation, and quality checks.
  • Support Azure Data Lake Storage, Azure SQL, and Azure-based data services.
  • Design workflow orchestration using Azure Data Factory or Microsoft Fabric / Foundry.
  • Build Python-based data services using Pandas, PyTorch, TensorFlow, and related libraries.
  • Develop API endpoints and microservices to support analytics and ML platform interoperability.
  • Implement logging, monitoring, performance tuning, and operational reliability.
  • Collaborate with data scientists, analysts, architects, and governance teams.
  • Apply data governance best practices for compliance, reproducibility, and auditability.

Desired Qualifications

  • A bachelor's degree, Ph.D., or equivalent professional experience in Data Science, Computer Science, Statistics, Engineering, or a related field.
  • Microsoft Data Engineer certification (for example DP-203 or DP-700) or a related Azure certification.
  • Knowledge of scalable, secure data engineering patterns in regulated environments.
  • Experience with Microsoft Fabric or Azure AI Foundry in production.
  • Experience building API endpoints or microservices (for example FastAPI or Flask) for analytics and ML platforms.
  • Experience supporting a federal agency or a regulated health, safety, or financial organization.

About the Company

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