Data Engineer Fabric

• Fabric Data Platform Development Building and maintaining data platforms using lakehouse and data warehouse workloads while creating scalable pipelines and structured data models.
• ETL and Data Pipeline Engineering Developing and optimizing ETL and ELT pipelines and dataflows to ensure reliable data ingestion, transformation, and processing.
  Reporting Data Model Enablement Supporting reporting capabilities by preparing curated datasets, semantic models, and optimized data structures for business analytics.
• Cross-Platform Data Integration Implementing and maintaining data integration and federation between cloud data environments to ensure secure and consistent data sharing.
• Platform Operations and Maintenance Handling operational support including debugging, incident resolution, performance tuning, and maintenance of existing data solutions.
• Data Architecture Improvement Refactoring legacy components and improving platform architecture, workflows, and automation practices.
• Security and Quality Compliance Ensuring data solutions comply with internal governance standards, security policies, and quality processes.
• Platform Evolution and Feature Adoption Implementing new platform capabilities and aligning data engineering solutions with evolving platform roadmaps.

Must-Have Skills:

• Enterprise Data Platform Experience Strong experience designing and operating modern cloud-based data platforms using integrated analytics and storage services.
• Lakehouse and Data Warehouse Workload Expertise Practical experience implementing and managing lakehouse and warehouse data workloads within modern data platforms.
• Data Lake Architecture Knowledge Understanding of centralized data lake architectures, unified storage concepts, and scalable data management principles.
• Data Pipeline Engineering Skills Strong experience building and managing ETL or ELT pipelines using modern data integration and orchestration tools.
• Reporting Data Model Optimization Experience preparing optimized datasets and semantic models for reporting and analytics platforms.
• Advanced SQL Development Skills Strong SQL expertise for designing efficient schemas, managing data transformations, and optimizing queries.
• Python Data Engineering Skills Strong programming experience using Python or similar languages for data processing and automation with test-driven development practices.
• Data Modeling Expertise Strong experience designing scalable and maintainable data models supporting analytics and operational reporting.

Nice-to-Have Skills:

• Software Architecture Knowledge Understanding of software architecture principles and common design patterns used in scalable data systems.
• Pipeline Orchestration Experience Familiarity with workflow orchestration tools used for scheduling and coordinating data pipelines.
• Data Quality Framework Knowledge Experience implementing data validation and quality frameworks to ensure reliability of data pipelines.
• Additional Cloud Platform Experience Hands-on experience working with services from other major cloud ecosystems for analytics, serverless processing, and machine learning.