PJoin our global Centre of Excellence as a subject matter expert (SME) for Agentic AI Services, collaborating with teams worldwide to drive innovation and excellence. As part of this central function, you will help shape, implement, and scale cutting-edge Agentic AI solutions across the organization and our clients. /ppThis hands-on role requires deep expertise in artificial intelligence, machine learning, and data to design, build, and deploy advanced Agentic AI-driven solutions tailored to clients' unique needs. /ppThe Data Engineer is a highly skilled and deep subject matter expert responsible for architecting, developing, and optimizing data pipelines and transformations that prepare data for analysis and consumption by Agentic AI systems. This expert plays a pivotal role in delivering high-quality, organized, and reusable datasets through scalable data engineering practices, leveraging Microsoft Fabric and the broader Microsoft ecosystem to create a modern, AI-ready data environment. /ppThis role analyzes diverse source systems and data structures, building robust data models and pipelines to support analytics, data science, and operational intelligence as the business evolves towards Agentic AI capabilities. Additionally, this role provides guidance, coaching, and mentorship to other data engineers and cross-functional teams. /ppstrongWhat You'll Be Doing /strong /polliLeads the design, implementation, and optimization of data pipelines using Microsoft Fabric, Azure Data Factory, Dataflows, and related Microsoft tools to ingest, transform, and deliver data fit for Agentic AI use-cases. /liliDevelops, automates, and maintains robust ETL/ELT processes that extract data from various sources—including on-premises and cloud—and integrate them into unified, structured formats within enterprise data lakes and warehouses. /liliAnalyzes business and technical requirements to design and develop scalable data models and data products supporting real-time, operational, and predictive analytics for Agentic AI adoption. /liliParticipates in translating conceptual and logical data models into efficient physical database schemas using Microsoft SQL, Azure Synapse, Microsoft Fabric Lakehouses, and related platforms, ensuring adherence to best practices and performance standards. /liliOversees migration and transformation of data between disparate systems (e.g., SAP, Oracle, Dynamics, SQL databases), ensuring secure, accurate, and reliable data provisioning for downstream AI workloads. /liliCollaborates with business analysts, data architects, and AI/ML engineers to ensure seamless delivery of data assets optimized for advanced analytics and Agentic AI workflows. /liliDefines, conducts, and oversees rigorous data validation and quality assurance processes, including the creation and execution of unit and integration test scenarios. /liliDevelops and maintains documentation for data pipelines, models, transformations, and migration activities, ensuring transparency and reproducibility. /liliAdvises on and implements data governance, metadata management, and lineage tracing in Microsoft Purview and Fabric, supporting compliance, discoverability, and readiness for AI. /liliIdentifies opportunities to automate data ingestion, transformation, and quality assurance tasks using scripting and modern orchestration practices. /liliCoaches and mentors less experienced data engineers and collaborates across multidisciplinary teams to foster a culture of modern data engineering and readiness for Agentic AI enablement. /li /olpstrongWhat You'll Bring Along /strong /pulliBachelor’s degree or equivalent in Computer Science, Software Engineering, Information Technology, or a related quantitative/engineering field. /liliMinimum 5-10 years of experience designing, building, and optimizing modern data solutions in Microsoft Azure, especially with Microsoft Fabric, Data Factory, and Synapse. /liliRelevant Microsoft certifications (e.g., Azure Data Engineer Associate, Microsoft Certified: Fabric Analytics Engineer) are highly regarded. /liliDeep expertise in data pipeline creation, transformation, and automation using Microsoft Fabric, Azure Data Factory, Power Query, Synapse Analytics, and Microsoft SQL-based solutions. /liliExcellent understanding of modern data engineering practices, including data lakehouse architectures, ETL/ELT design, and data modeling in the context of preparing data for AI systems. /liliStrong grasp of both logical and physical data modeling concepts, with experience implementing schemas that optimize data utilization by analytics and AI platforms. /liliAnalytical mindset with robust problem-solving abilities, capable of translating business requirements into scalable data engineering solutions. /liliDemonstrated programming skills in SQL, Python, PowerShell, and (where relevant) Dataflow/Spark languages within the Microsoft data engineering ecosystem. /liliFamiliarity with data governance, lineage, and quality assurance practices in Microsoft Purview and related Microsoft tools. /liliExpertise with multiple database types, including Azure SQL, Fabric Lakehouse, Azure Data Lake, and third-party sources (SAP, Oracle, etc.). /liliExperience with real-time and batch data processing, scaling data pipelines to support high-volume/complex analytics requirements. /liliSkilled in mentoring and guiding less experienced team members to adopt best-in-class cloud data engineering and tools. /liliDemonstrated experience in ingesting, transforming, and structuring data from large and complex, multi-terabyte data sources for analytics and AI/ML applications. /liliProven success in automating and scripting data pipelines (Python, PowerShell, SQL, etc.) for scalable, repeatable ingestion and transformation both on-premises and in cloud. /liliExperience with various database and data warehouse platforms (Azure SQL, Fabric Lakehouse, SAP, Oracle, etc.) and integrating, migrating, and validating data across applications. /liliFamiliarity with big data tools (Hadoop, Spark) as integrated within the Microsoft Azure ecosystem is preferred. /liliExperience with end-user tools such as Power BI and Excel (pivots, macros) and supporting quality assurance for downstream reporting and analytics. /liliTrack record of supporting enterprise migration to AI-driven analytics solutions and mentoring teams in adopting modern Microsoft data engineering practices. /liliExcellent command of both spoken and written English. /li /ulh3Seniority level /h3ulliMid-Senior level /li /ulh3Employment type /h3ulliFull-time /li /ulh3Job function /h3ulliInformation Technology /li /ulh3Industries /h3ulliIT Services and IT Consulting /li /ul #J-18808-Ljbffr