The role involves designing scalable data pipelines and architectures using Microsoft Fabric, client engagement for requirements gathering, and optimizing data solutions for analytics and reporting.
1. Role Overview
We are seeking a highly skilled Microsoft Fabric Data Engineer with strong expertise in building scalable data platforms and engaging directly with US-based clients. The ideal candidate will play a key role in designing, developing, and optimizing enterprise-grade data solutions, with a focus on data modeling, reporting optimization, and modern analytics architectures.
This role requires a blend of technical depth, business understanding, and client-facing communication skills.
Key Responsibilities
Data Engineering & Platform Development
- Design and implement end-to-end data pipelines using Microsoft Fabric (Data Factory, Lakehouse, Notebooks)
- Build scalable data architectures leveraging medallion (Bronze/Silver/Gold) patterns and lakehouse models [GSL MS Fab...ument V1.3 | Word]
- Develop robust and optimized ETL/ELT pipelines for structured and semi-structured data
- Integrate data from multiple enterprise sources (SQL Server, APIs, cloud platforms)
Data Modeling & Reporting
- Design and develop semantic models and data models for reporting and analytics [ImpactNOW Proposal | PowerPoint]
- Build optimized data models (facts, dimensions, relationships) for Power BI reporting
- Enable Direct Lake / real-time analytics scenarios and reporting performance optimization
- Work closely with BI teams to ensure high-performing dashboards and reports
Client Engagement (US Clients)
- Interface directly with US stakeholders to understand business requirements and reporting needs
- Participate in requirement gathering, solution walkthroughs, and design discussions
- Translate business requirements into scalable technical solutions
- Provide regular status updates, demos, and technical insights to client teams
Architecture & Best Practices
- Define and implement Fabric-based data architectures aligned with enterprise standards
- Ensure data governance, data quality, and security best practices
- Optimize performance, scalability, and cost across data pipelines and storage
- Collaborate with architects and cross-functional teams
Requirements
Core Technical Skills
Strong experience with Microsoft Fabric / Azure Data Platform
Hands-on experience with:
- Fabric Lakehouse, Data Factory, Dataflows / Pipelines
- Power BI (Data modeling, DAX, performance tuning)
- SQL, Python, PySpark
- Expertise in data modeling (dimensional modeling, star/snowflake schemas)
- Experience building scalable data pipelines and distributed processing systems
Data Platform & Integration
Experience with:
- Azure Data Factory / Synapse / Databricks
- Data ingestion, transformation, and orchestration
- Understanding of data lake, data warehouse, and lakehouse architectures
Engineering Practices
- Experience with CI/CD, version control, and deployment pipelines
- Strong debugging, performance tuning, and problem-solving skills
Preferred Qualifications
- Experience with Direct Lake / Real-time intelligence (RTI) scenarios [Fabric + RTI | PowerPoint]
- Exposure to API integrations and application-level data consumption [GSL MS Fab...ument V1.3 | Word]
- Certifications in Microsoft Azure / Fabric / Power BI
- Experience in industry domains (Healthcare, Retail, Finance)
Experience Requirements
- 5–10 years of experience in Data Engineering
- Minimum 2+ years of experience in Microsoft Fabric or modern analytics stack
- Demonstrated experience in client-facing roles with US stakeholders [Re: Job De...a engineer | Outlook]
Key Competencies
- Strong analytical and problem-solving capability
- Business-oriented thinking with technical depth
- Ability to work independently and in global delivery teams
- Proactive mindset with ownership and accountability
Nice-to-Have
- Exposure to AI/ML integration within Fabric ecosystem
- Experience working in consulting or delivery-led environments
- Familiarity with Agile delivery models
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