Job Description - Data Engineer and Agentic AI Lead
Overview
We are seeking a Microsoft Fabric Data Engineer with Agentic AI experience to design, build, and maintain scalable data solutions within the Microsoft Fabric ecosystem. This role is responsible for developing robust data pipelines, implementing Medallion architecture (Bronze, Silver, Gold layers), and ensuring high-quality, analytics-ready datasets.
The ideal candidate will have hands-on experience with Microsoft Fabric components (Data Factory, OneLake, Lakehouse, Warehouse, and Power BI), strong data engineering fundamentals, and the ability to support advanced analytics and AI initiatives.
Key Responsibilities
Design, develop, and maintain end-to-end data pipelines using Microsoft Fabric (Data Factory, Pipelines, Notebooks)
Implement and manage Medallion architecture (Bronze, Silver, Gold layers) to ensure data quality, governance, and usability
Ingest, transform, and integrate data from multiple structured and unstructured sources
Optimize data workflows for performance, scalability, and cost efficiency
Build and maintain Lakehouse and Data Warehouse solutions within Fabric
Ensure data reliability through monitoring, logging, and error-handling mechanisms
Collaborate with stakeholders to translate business requirements into scalable data solutions
Enforce data governance, security, and compliance best practices
Document data models, pipelines, and system architecture
Contribute to roadmap planning and platform evolution
Database & Power BI Oversight
Design enterprise-grade data models optimized for Power BI and analytics workloads
Oversee creation and management of semantic models and datasets within Fabric
Oversee dataset performance, refresh strategies, and capacity management in Power BI
Implement data modeling best practices (star schema, normalization where appropriate)
Support development of dashboards and reports by providing curated, high-quality datasets
Manage access control, row-level security (RLS), and data lineage visibility
Manage Power BI capacity, dataset refresh strategies, and scalability considerations
Collaborate with BI developers to optimize DAX performance and reporting efficiency
Monitor usage and adoption metrics to improve data accessibility and usability
AI Readiness & Advanced Analytics
Prepare and structure data to support AI/ML use cases within Microsoft Fabric and Azure ecosystem
Enable feature engineering by delivering clean, enriched, and well-governed datasets
Support integration with AI tools such as Azure Machine Learning, Fabric Data Science, and Copilot experiences
Implement data pipelines that support real-time or near real-time analytics where needed.
Ensure datasets are scalable and aligned with AI model training requirements.
Promote best practices for data versioning, reproducibility, and experimentation.
Qualifications
Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
7+ years of experience in data engineering or related roles.
Hands-on experience with Microsoft Fabric or closely related tools (Azure Synapse, Azure Data Factory, Power BI).
Strong expertise in Medallion architecture and modern data lake/lakehouse patterns.
Proven experience building and maintaining data pipelines (ETL/ELT).
Proficiency in SQL, Python, and/or Spark.
Experience with Lakehouse architectures and distributed data processing.
Strong understanding of data modeling and data warehousing concepts.
Desired Skills & Competencies
Experience with OneLake, Delta Lake, and Fabric-native workloads.
Experience with Data Agents, Copilot Studio and Microsoft Foundry
Familiarity with CI/CD pipelines for data solutions.
Power BI adoption and user satisfaction across business units.
Delivery of AI-ready datasets and agentic AI pilot outcomes
Security compliance and incident prevention
Key Competencies
Strong problem-solving and analytical thinking
Attention to detail and data quality focus
Ability to work cross-functionally with technical and business teams
Excellent communication and documentation skills
Continuous learning mindset in evolving data and AI technologies
Performance Metrics
Data integrity and availability across all departments
System uptime and query performance
Power BI adoption and user satisfaction across business units
Reduction in time-to-action based on data insights
Successful onboarding and reliability of third-party integrations
Delivery of AI-ready datasets and agentic AI pilot outcomes
Security compliance and incident prevention
Adoption of best practices as informed by industry trends
This role is essential for Garan Apparel's enterprise data transformation, integrating Azure and Microsoft Fabric with best practices in data, security, AI readiness, and team collaboration—while ensuring that every user, from executive to analyst, can understand, trust, and act on data with confidence.
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