Role Overview :

We are seeking a highly skilled and motivated AI Data Engineer to join our dynamic team. In this role, you will be responsible for designing, building, and maintaining the data infrastructure that powers our AI and machine learning initiatives. You will collaborate closely with data scientists, machine learning engineers, and software developers to ensure the efficient and reliable flow of data for model training, deployment, and monitoring. Your work will directly impact the performance and scalability of our AI solutions, ultimately driving better business outcomes and enhancing user experiences.

Key Responsibilities :

- 3+ years of hands-on experience in MLOps and/or AIOps, ideally within an Azure cloud environment

- Demonstrated expertise with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry

- Design and implement robust data pipelines for ingestion, processing, and storage of large-scale datasets, ensuring data quality and consistency for AI/ML models.

- Develop and maintain scalable data infrastructure on Azure cloud platform, optimizing for performance, cost, and security to support AI/ML workloads.

- Collaborate with data scientists and machine learning engineers to understand data requirements and translate them into efficient data engineering solutions, accelerating model development and deployment.

- Implement MLOps best practices for model deployment, monitoring, and retraining, ensuring the reliability and performance of AI models in production.

- Automate data engineering tasks and infrastructure management using Infrastructure as Code (IaC) principles, improving efficiency and reducing manual effort.

- Contribute to the development of AIOps solutions for monitoring and managing AI infrastructure, proactively identifying and resolving issues to minimize downtime.

- Troubleshoot and resolve data-related issues in a timely manner, ensuring data availability and integrity for critical AI applications.

Required Skillset :

- Demonstrated expertise in designing and implementing data pipelines using tools such as Apache Spark, Apache Kafka, and Azure Data Factory.

- Proven ability to build and manage data infrastructure on Azure cloud platform, including Azure Data Lake Storage, Azure Databricks, and Azure Synapse Analytics.

- Strong understanding of MLOps principles and experience with tools such as MLflow, Kubeflow, or Azure Machine Learning.

- Experience with AIOps concepts and tools for monitoring and managing AI infrastructure.

- Excellent programming skills in Python or Scala, with a focus on data manipulation and processing.

- Solid understanding of data modeling, data warehousing, and database technologies.

- Ability to communicate effectively with both technical and non-technical audiences, explaining complex data concepts in a clear and concise manner.

- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.