Azure Senior Data Lead - HCLTech

Key Responsibilities

• Define and implement enterprise MLOps strategy, standards, and best practices across Azure and Databricks environments.
• Lead the design, deployment, and operationalization of end‑to‑end ML lifecycle solutions, including data ingestion, feature engineering, model training, and serving.
• Architect and maintain scalable, secure, and compliant ML pipelines using Kubernetes, CI/CD, and MLflow for model tracking and reproducibility.
• Collaborate with data scientists, data engineers, and business stakeholders to translate business requirements into technical solutions and ensure alignment with organizational goals.
• Drive continuous improvement of model monitoring, performance tracking, and automated retraining workflows to sustain high model quality.

Requirements

• Extensive experience with Azure services (Azure ML, Azure Data Factory, Azure Synapse) and Databricks for large‑scale data processing.
• Proven expertise in MLOps practices, including CI/CD pipelines, containerization, and model governance.
• Strong programming skills in Python and familiarity with Kubernetes, Docker, and MLflow.
• Excellent communication and stakeholder management abilities, with a track record of delivering complex AI projects.
• Knowledge of security, compliance, and data privacy best practices in cloud environments.