Analytics Engineer I

• AI & Intelligent Systems Engineering: Design and deploy enterprise AI solutions using LLMs, RAG architecture, and intelligent agents aligned with ECC business needs.
• Copilot & Agent Development: Build and maintain copilots and AI agents using Microsoft Copilot Studio and Microsoft Agents SDK, integrating workflows, guardrails, and telemetry.
• Computer Vision & Detection Models: Develop, train, and deploy computer vision models for object detection, classification, and image analysis to support operational, safety, and analytical use cases.
• Data Foundations for AI: Engineer and manage Azure‑based data pipelines that power AI retrieval, embeddings, and analytics workloads.
• Automation & AI Integration: Develop Python‑based automation and integrations for APIs, document ingestion, embeddings, and AI pipeline orchestration.
• Analytics & Decision Enablement: Enable AI‑driven insights by supporting trusted semantic models and datasets used across reporting, copilots, and executive workflows.
• Cross‑Functional Collaboration: Partner with business and technical teams to define AI use cases, data requirements, and success metrics.
• Governance, Quality & Observability: Ensure AI and data solutions meet standards for security, reliability, documentation, transparency, and responsible use.
• Documentation & Production Support: Maintain clear technical documentation and support production AI systems during deployments and critical business cycles.

• Bachelor’s degree in computer science, Information Systems, Engineering, Data Science, or a related field with at least 2 years of professional experience in data engineering, BI engineering, or analytics engineering; or a master’s degree in one of these fields with at least 1 year of professional experience.
• Strong SQL includes window functions, performance tuning, and relational modeling.
• Hands‑on experience with Azure (AI Search, ADF/Synapse, ADLS, Azure SQL, Key Vault, Functions, Fabric, Purview).
• Hands-on experience with Computer vision models for classification, detection and segmentation using cloud services or offline models
• Proven experience with LLMs, RAG architecture, embeddings, prompt engineering, and evaluation techniques in an enterprise setting.
• Proficiency in Python for data engineering, AI pipelines, APIs, document processing, and automation.
• Experience building copilots or intelligent agents using Copilot Studio, Microsoft Agents SDK, or comparable AI orchestration frameworks.
• Experience with Git and CI/CD pipelines.
• Understanding of data quality, observability, and structured documentation.

ECC targeted salary range for US locations average is $75,762 to $103,840 annually. Actual salary offered may be affected by education, training, certifications, experience, skills, level of responsibility, and location.