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They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.\nKey Responsibilities: \nDesign and implement scalable and secure data pipelines using Microsoft Fabric components (Data Factory in Fabric, Dataflows Gen2, Eventstreams, and Synapse Data Engineering).\n\nBuild and manage lakehousesand warehouses within OneLake, ensuring performance, scalability, and data governance compliance.\n\nCollaborate with business and analytics teams to gather data requirements and translate them into reliable datasets for reporting and advanced analytics.\n\nDevelop and optimizenotebooks (PySpark) for data transformation and machine learning workflows within Microsoft Fabric.\n\nSupport Power BI semantic models and implement real-time or near-real-time analytics.\n\nEnsure data quality, lineage, and observability by leveragingMicrosoft Purview or Fabric’s native monitoring capabilities.\n\nImplement CI/CD pipelines and manage deployment of data assets using DevOps for Fabric artifacts.\n\nCollaborate closely with data architects, analysts, and platform engineers to contribute to the modern data architecture roadmap.\n\nStay current with developments in Microsoft Fabric and related technologies to provide recommendations and continuous improvement.\n\nBachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.\n\n8+ years of experience in the Data & Analytics field\n\nProficiencyin SQL, PySpark, and Power BI.\n\nExperience with Microsoft OneLake, Dataflows Gen2, Synapse Engineering in Fabric, and DirectLakeconnectivity.\n\nFamiliarity with DataOpspractices, version control (e.g., Git), and automated deployment pipelines.\n\nUnderstanding of data modeling (dimensional/star schema) and performance optimization techniques.\n\nKnowledge of data governance, security, and compliance within the Microsoft ecosystem.\n\nExperience integrating data from diverse sources including APIs, flat files, relational and NoSQL databases.\n\nEducation (if blank, degree and/or field of study not specified)\nDegrees/Field of Study required:Degrees/Field of Study preferred:Certifications (if blank, certifications not specified)\nRequired Skills\nOptional Skills\nAccepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation {+ 24 more}Desired Languages (If blank, desired languages not specified)\nTravel Requirements\nNot SpecifiedAvailable for Work Visa Sponsorship?\nNoGovernment Clearance Required?\nNoJob Posting End 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