Job Summary

Data Engineer with AI capabilities

Key Responsibilities

• Experience with Microsoft Copilot Studio, including agent creation, orchestration, publishing, and extension through custom skills
• Power Platform integration expertise, including custom connectors and end‑to‑end solution deployment
• Strong Databricks experience, including Unity Catalog, Delta Lake, feature engineering, and data pipelines
• Data engineering and data modeling proficiency, with deep understanding of ETL/ELT workflows and scalable data architectures
• Familiarity with Responsible AI, security, and privacy best practices in enterprise AI systems
• Proficient in applying common design patterns, ability to communicate design ideas effectively.
• Must have a disciplined, methodical, minimalist approach to designing and constructing layered software components that can be embedded within larger frameworks or applications.
• Hands-on experience in deploying machine learning pipelines with Azure Machine Learning SDK. Knowledge of enterprise SaaS complexities including security/access control, scalability, high availability, concurrency, online diagnoses, deployment, upgrade/migration, internationalization, and production support.
• Knowledge of data engineering and transformation tools and patterns such as DataBricks, Spark, Azure Data Factory.

Skill Requirements

• Minimum 5 years’ experience in Object Oriented Design and Programming and Python development.
• Experience implementing machine learning frameworks and libraries
• Development experience with a JavaScript framework, experience building machine learning pipelines in Microsoft Azure Machine Learning service
• Experience developing cloud first solutions using Microsoft Azure Services 
• Experience building multi‑agent LLM solutions using Microsoft Azure AI, Databricks, or comparable ecosystems, including tool/function calling, orchestration, guardrails, evaluators, and related capabilities.
• Strong NLP expertise, including text processing, embedding generation, semantic search, and retrieval optimization.
• Proficiency with Retrieval‑Augmented Generation (RAG) patterns, vector indexing, grounding strategies, and metadata‑driven retrieval.

Other Requirements

Knowledgeable in all aspect of Data Engineering in Azure eco system.  Oil and Gas experience is preferred.  Working knowledge of physical security and building data products.