Senior Data Engineer

NO VISA CANDIDATES / NO AGENCIES / NO THIRD PARTIES

Position Summary We are seeking a highly skilled Data Engineer to design, build, and govern enterprise data platforms that support operational applications, business analytics, and AI initiatives. This role will develop scalable data architectures using Microsoft Fabric tools, SQL Server, Dataverse, and Azure services to deliver trusted, AI-ready data assets across the organization. The ideal candidate combines expertise in data engineering, dimensional and operational modelling, application integration, analytics enablement, and modern AI data architectures. This individual will partner closely with business stakeholders, application teams, architects, analysts, and AI initiatives to create reusable, governed, and scalable data products. Key Responsibilities Design and implement enterprise data architectures using Microsoft Fabric, OneLake, Lakehouse, Warehouse, and SQL Server technologies. Build and maintain scalable ingestion frameworks from: Dataverse SQL Server REST APIs SaaS applications Flat files and SFTP sources Develop Fabric Data Pipelines, Dataflows Gen2, Notebooks, and Semantic Models. Implement bronze, silver, and gold data layer architectures. Optimize data pipelines for performance, reliability, scalability, and cost management. Application Data Modeling Design Dataverse and operational application data models. Support application solution teams with: Integration patterns Design APIs and data contracts that support application interoperability. Partner with development teams to ensure applications generate high-quality analytical and AI-ready data. Analytics Data Modeling Design dimensional, star-schema, and semantic models. Create business-friendly analytical structures supporting Power BI and self-service analytics. Build conformed dimensions and enterprise metrics. Develop data marts and analytical products that drive reporting consistency. Support Data Lake and enterprise semantic model strategies. Design and prepare AI-ready datasets. Curate structured, semi-structured, and unstructured data assets for AI use cases. Build data pipelines that support: Retrieval-Augmented Generation (RAG) AI agents Semantic search Machine learning initiatives Implement metadata, lineage, and semantic enrichment patterns to improve AI effectiveness. Support AI model training, evaluation, and operationalization workflows. Data Governance & Quality Implement data quality monitoring and remediation processes. Define and maintain: Metadata Data ownership Data stewardship processes Ensure compliance with security, privacy, and regulatory standards. Integration Engineering Design and implement integrations using: Dataverse Fabric Power Platform Logic Apps REST APIs Event-driven architectures Develop near real-time and batch integration patterns. Support change data capture (CDC) and data synchronization solutions. Performance & Operational Excellence Monitor and optimize Fabric workloads. Tune SQL Server databases, queries, and data models. Establish DevOps and CI/CD practices for data assets. Develop monitoring, alerting, and observability processes. Support production operations and incident resolution. Required Skills Advanced Microsoft Fabric SQL Server

T-SQL

Dataverse Power BI Semantic Models Data Modeling ETL / ELT Design Data Warehousing Lakehouse Architecture Strong Python Spark / PySpark Fabric Notebooks Dataflows Gen2 REST APIs Power Platform Knowledge Of Medallion Architecture OneLake Master Data Management Microsoft Purview RAG Patterns Data Governance Preferred Experience Microsoft Fabric implementation experience. Dataverse data architecture and integration experience. Healthcare, pharmacy, financial, or operational analytics experience. Designing enterprise-scale semantic and dimensional models. Working with both operational application data and analytical reporting environments. #J-18808-Ljbffr 7N