Azure Data Engineer - ETL/PySpark

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.

(ref:hirist.tech)