Endurance IT Services · 14 hours ago
Principal Advanced Analytics Engineer
Endurance IT Services is supporting a client in advancing their enterprise-wide AI initiatives. We are seeking a Principal Advanced Analytics Engineer who will lead the technical vision and execution of modern AI, ML, and BI solutions built on Microsoft technologies.
Responsibilities
Collaborate with business stakeholders and senior IT leadership to design, build, and deploy predictive and prescriptive AI/ML models that align with organizational goals
Establish and maintain engineering best practices, architectural guidelines, and quality frameworks for advanced analytics solutions
Implement end‑to‑end MLOps processes, including CI/CD pipelines, model versioning, automated testing, observability, drift monitoring, and retraining workflows within Microsoft Fabric and Azure ML
Promote Responsible AI principles by ensuring model fairness, transparency, explainability, and compliance with regulatory and internal governance standards
Design and optimize enterprise data models—such as dimensional and star schemas—to support business intelligence, automation, and AI agent workloads
Partner with analytics and insights teams to deliver high‑performance, scalable, and reliable data products
Ensure adherence to security, data‑access governance, lineage tracking, and enterprise privacy requirements
Stay ahead of emerging AI, ML, and BI capabilities; evaluate new technologies and introduce innovative tools and approaches to the organization
Provide mentorship to data and analytics engineers, fostering skill development, technical growth, and effective problem-solving practices
Qualification
Required
8+ years of experience in data engineering, analytics, or related fields, including 3+ years designing AI/ML architectures or enterprise-grade machine learning solutions
Strong communication, collaboration, and customer engagement skills, with a demonstrated ability to work closely with non‑technical stakeholders
Advanced proficiency across the Microsoft data and analytics ecosystem, including Microsoft Fabric, Azure Machine Learning, Azure Synapse, Azure Data Factory, Power BI, Lakehouse/Warehouse architectures, Spark, Python, Notebooks, Pipelines, and Dataflows
Hands‑on experience developing, validating, and deploying predictive and generative AI models—including large language models—using Fabric and Azure ML
Expertise in building dimensional and star‑schema data models to support analytics, reporting, and AI-driven applications
Proven experience implementing MLOps practices such as CI/CD for ML, automated monitoring, and model lifecycle management
Strong understanding of data governance, including security, access controls, lineage, and compliance with internal and external standards