Azure Data Engineer
First seen by Alion on Aug 19, 2026.
About SGA :
SG Analytics is a Great Place to Work (GPTW) certified global leader in research and contextual analytics. We empower enterprises with data-driven insights, leveraging advanced AI, machine learning, and cloud technologies to solve complex business challenges in a highly collaborative and innovative environment.
Role & responsibilities :
- Deploy and monitor production AI models across Azure services ensuring system availability and reliability.
- Implement robust telemetry frameworks to track model performance, data drift, and inference metrics.
- Build and maintain automated MLOps pipelines for continuous integration and lifecycle management using Azure ML and GitHub Actions.
- Manage end-to-end model upgrades including APIs and UIs with structured rollout, version control, and rollback mechanisms.
- Optimize cloud infrastructure performance and compute costs through rigorous profiling, testing, and tuning of inference pipelines.
- Ensure compliant change management practices across all deployments to meet enterprise security and auditability standards.
- Collaborate with cross-functional teams including AI Developers, Cloud Architects, and Governance leaders to scale operations.
Preferred candidate profile :
Experience :
- 4+ to 12 years of professional experience in MLOps and/or AIOps roles. Consulting background is highly preferred.
Education :
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field.
Technical Expertise :
- Strong proficiency in Azure cloud tools including Azure ML, Synapse, Data Lake, Cosmos DB, and Azure AI Foundry.
Automation & Testing :
- Hands-on experience with workflow design (Prompt flow), Azure DevOps, and inference performance testing tools like Locust or K6.
Advanced ML Concepts (Assumed) :
- Familiarity with post-training techniques like fine-tuning, instruction tuning, model evaluation metrics, and A/B testing frameworks.
Skills
Python, Azure Data Factory, PySpark, Azure Databricks, SQL, Machine Learning, Data Engineering, DataLake, Cosmos DB, ETL