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Fabric Data Engineer

Confidential

We are a company that helps organizations transform business performance through advanced analytics, cloud technologies, AI, and digital engineering. We partner with global enterprises to build scalable data platforms that support business intelligence, automation, and AI-driven decision making. Our focus is on delivering enterprise-grade solutions that turn complex data into reliable, high-value outcomes for modern businesses. The team works on large-scale technology programs where data architecture, platform engineering, and analytics capabilities must come together to improve speed, quality, and decision-making. This role sits within an environment that values strong technical execution, collaboration, and continuous improvement across data delivery. The organization is looking for a Fabric Data Engineer who can help build modern Lakehouse-based platforms using Microsoft Fabric. The work will directly support reporting, advanced analytics, and AI/ML use cases. Company Proof Points Partners with global enterprises to build scalable data platforms that power business intelligence, automation, and AI-driven decision making. - Works across advanced analytics, cloud technologies, AI, and digital engineering to support business transformation. - Delivers enterprise-scale data solutions that serve reporting, analytics, and AI/ML initiatives. Company Practices & Ways of Working Collaborates closely with business stakeholders, data scientists, and engineering teams to deliver high-quality solutions. - Operates in a collaborative global delivery environment with strong emphasis on continuous learning and career growth. - Values troubleshooting, optimization, and reliability in data platform delivery. About the Role This role owns the design, build, and optimization of enterprise-scale data platforms using Microsoft Fabric. The focus is on creating Lakehouse architectures, scalable ETL/ELT pipelines, and high-performance data solutions that enable reporting, advanced analytics, and AI/ML initiatives. The engineer will work across ingestion, transformation, orchestration, and integration layers to keep data assets reliable, governable, and ready for consumption. Success in this role means delivering stable platforms that improve data availability, support modern analytics workflows, and accelerate downstream decision-making. The position also requires close collaboration with stakeholders and technical teams to ensure data solutions stay aligned with business needs and performance expectations. Key Responsibilities Design, develop, and maintain scalable data platforms using Microsoft Fabric so enterprise data can be delivered reliably at scale for reporting and analytics. - Build and optimize ETL/ELT pipelines with Data Factory, Spark notebooks, and PySpark to improve data movement, transformation speed, and repeatability. - Develop Lakehouse solutions using OneLake and Delta Tables to create a structured foundation for governed, high-performance data access. - Implement robust ingestion, transformation, and orchestration workflows that keep data pipelines dependable, observable, and ready for production use. - Support AI/ML initiatives by preparing curated datasets and feature‑engineered inputs that improve model readiness and analytical value. - Integrate Microsoft Fabric with Power BI, semantic models, and enterprise analytics platforms so business teams can consume trusted data efficiently. - Ensure governance, quality, security, and compliance across data assets to reduce risk and protect the integrity of enterprise data. - Monitor, troubleshoot, and optimize pipeline performance, scalability, and reliability to keep data services stable under changing demand. Microsoft Fabric expertise with hands‑on experience in building enterprise data platforms, Lakehouse patterns, and operational analytics workflows. - Strong skills in Data Factory, Spark notebooks, and PySpark to design and support scalable ETL/ELT processing across large datasets. - Advanced SQL and distributed data processing knowledge to transform, model, and query data efficiently across modern cloud environments. - Practical experience with OneLake, Delta Tables, and data modeling best practices to build structured and reusable data foundations. - Working knowledge of data governance, security, quality management, and performance tuning to keep platforms reliable and compliant. - Experience integrating Power BI, semantic models, and enterprise reporting platforms so data products serve business users effectively. - Familiarity with Azure Data Services, CI/CD, Git, and Microsoft Purview to support disciplined engineering and controlled delivery. Additional Plus Experience supporting enterprise AI and analytics platforms, especially where data preparation directly influences downstream model or insight quality. - Exposure to DevOps practices for data engineering, including automated delivery, version control, and release discipline. - Background in large-scale cloud transformation programs where multiple teams depend on the same data platform. What You’ll Bring A solid track record of delivering data engineering solutions across cloud platforms, with the judgment to balance scalability, reliability, and business usability. - Strong technical ownership across ingestion, transformation, orchestration, and optimization so data pipelines are dependable from source to consumption. - The ability to partner with analysts, data scientists, and engineers to translate business needs into well‑governed data products. - A continuous‑improvement mindset that uses troubleshooting, debugging, and performance tuning to raise platform quality over time. Why Join Us Join a team building enterprise‑scale data platforms that directly support analytics, automation, and AI‑driven decision making. This is a chance to work with Microsoft Fabric in a setting where architecture quality, pipeline reliability, and business impact matter every day. You will contribute to a platform that enables faster reporting, stronger governance, and better data readiness for advanced analytics and AI/ML use cases. The role offers exposure to cloud transformation work, collaboration with global teams, and opportunities to deepen your skills across modern data engineering practices. If you want to work on meaningful data problems at enterprise scale and help shape reliable, high‑value platforms, this environment offers the scope and complexity to grow. What We Offer Work on enterprise‑scale Microsoft Fabric implementations that have direct impact on analytics and decision‑making. - Exposure to AI, analytics, and cloud transformation initiatives in a collaborative global delivery environment. - Continuous learning and career growth opportunities in a role that values technical depth and platform reliability. #J-18808-Ljbffr

Vacancy posted 2 days ago
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