AI / Data Engineer (Mid-Level): Python, Azure Data & ML Pipelines

About the role

At Intertwine Associates we show up ready to work, partnering with organizations across government, management, strategy, and technology to deliver operational efficiency and measurable impact. We focus on practical solutions, tailored frameworks, and innovation that drives meaningful results. This is a remote position supporting a federal agency or other client's enterprise data management environment as a mid‑level AI/Data Engineer.

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.

Requirements

• 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.

Qualifications

• Bachelor's, 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.

Skills

Technical skills highlighted include Python (Pandas, NumPy, scikit-learn, PyTorch, TensorFlow), SQL, Azure (Data Lake Storage, SQL, Data Factory, Fabric, AI Foundry), ETL development, API/microservice development (