<p>About the Role</p><p>Our client is seeking an AI Data Engineer to design, build, and optimize data and AI pipelines within a modern Azure Databricks Lakehouse environment. This role sits at the intersection of data engineering, machine learning enablement, and cloud‑scale analytics, supporting advanced AI initiatives across the organization.</p><p>You will work closely with data scientists, ML engineers, and business stakeholders to deliver high‑quality data products, feature pipelines, and production‑ready AI workflows that power predictive analytics, generative AI, and operational intelligence</p><p><br></p><p>Key Responsibilities</p><ul><li>Design and build scalable data pipelines using Azure Databricks, Spark, and Delta Lake</li><li>Develop and optimize ETL/ELT workflows across Azure Data Lake Storage</li><li>Implement AI‑ready data architectures including feature stores and vector stores</li><li>Productionize ML and generative AI models using MLflow and Databricks Model Serving</li><li>Create and maintain medallion architecture for analytics and AI workloads</li><li>Develop SQL and PySpark transformations for large‑scale datasets</li><li>Integrate Azure services such as Data Factory, Event Hub, and Functions</li><li>Ensure data governance and security using Unity Catalog and RBAC</li><li>Monitor and optimize Databricks clusters for cost and performance</li><li>Support CI/CD automation using Azure DevOps</li></ul><p><br></p>

<p>Required Qualifications</p><ul><li>Hands‑on experience with Azure Databricks including Spark, Delta Lake, and MLflow</li><li>Strong proficiency in Python and SQL</li><li>Experience with Azure data services such as Data Factory, Data Lake, and Synapse</li><li>Background in data engineering supporting analytics, ML, or AI applications</li><li>Understanding of machine learning pipelines and feature engineering</li><li>Experience with distributed data processing using Spark</li><li>Knowledge of CI/CD practices in Azure DevOps</li><li>Strong problem‑solving and communication skills</li></ul><p>Preferred Qualifications</p><ul><li>Experience with vector databases such as Pinecone or Azure AI Search</li><li>Familiarity with generative AI workflows including embeddings and RAG</li><li>Exposure to Lakehouse architecture in enterprise environments</li><li>Oil and gas or industrial domain experience</li></ul><p><br></p>

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