We are seeking an experienced AI Data Engineer with strong hands-on expertise in Microsoft Fabric, Azure Data Services, and modern data engineering practices. This role will be responsible for designing, building, and maintaining scalable data platforms that support advanced analytics, AI, and machine learning initiatives across the organization.
The ideal candidate combines deep technical knowledge with a strong understanding of data architecture, governance, and AI integration, working closely with cross-functional teams to deliver high-value data solutions.
Key Responsibilities:
Data Engineering & Architecture
Design, build, and maintain scalable data pipelines using Microsoft Fabric (Data Factory, Dataflows, Lakehouse, Warehouse, OneLake).
Develop robust data ingestion, transformation, and orchestration workflows leveraging Azure Data Factory, Azure Databricks, Azure Synapse, and Azure Functions.
Implement and optimize Delta Lake architectures for both structured and unstructured data.
Create reusable and high-quality data products to support analytics, AI, and machine learning use cases.
AI & Advanced Analytics Integration
Collaborate with Data Scientists and ML Engineers to operationalize AI/ML models using Azure Machine Learning, Microsoft Fabric Data Science, or Databricks.
Prepare, curate, and feature-engineer datasets optimized for AI and ML workloads.
Automate MLOps processes, including model deployment, monitoring, and lifecycle management.
Governance, Quality & Security
Implement data quality, observability, monitoring, and lineage frameworks using Microsoft Fabric and Azure Purview.
Ensure compliance with data governance, privacy, and security standards.
Manage CI/CD pipelines for data solutions using Azure DevOps or GitHub.
Collaboration & Stakeholder Engagement
Work closely with business analysts, product owners, and domain experts to understand requirements and translate them into scalable data solutions.
Maintain clear and up-to-date documentation of data sources, models, pipelines, and best practices.
Provide technical guidance and mentorship to junior data engineers and developers.
Required Skills & Qualifications
10+ years of experience as a Data Engineer, AI Engineer, or in a similar role.
Strong hands-on experience with Microsoft Fabric, including Lakehouse, Data Engineering, Data Factory, and Data Pipelines.
Advanced expertise in Azure Data Services, including:
Azure Data Factory
Azure Databricks / Apache Spark
Azure Synapse Analytics / SQL Pools
Azure Storage (ADLS Gen2)
Azure Functions
Azure Machine Learning
Strong proficiency in Python and SQL for data processing and transformation.
Proven experience designing and implementing data lakehouse architectures and Delta Lake pipelines.
Solid understanding of DevOps and MLOps practices, including version control, testing, and automated deployments.
Experience with data governance frameworks, preferably using Azure Purview or Microsoft Fabric governance capabilities.