About Fusemachines
Fusemachines is a 12+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.
Type: Full-time, Remote
About the role
This is a full-time, dedicated position for a Data Engineer with specialized expertise in Microsoft Fabric and the Azure ecosystem to support a major data architecture modernization for a key client in the Biotech industry.
In this role, you will support a long-standing initiative to modernize and scale the client's analytics capabilities. Your primary objective will be to drive the migration from an existing Azure environment, currently serving approximately 500 Power BI users, to Microsoft Fabric. Key deliverables include architecting the migration strategy, optimizing platform performance for high concurrency, and integrating GXP manufacturing and quality data into the platform to support critical regulatory data streams.
Qualification / Skill Set Requirement:
Core Technical Expertise:
5+ years of hands-on data engineering experience with deep expertise in Microsoft Fabric and the broader Azure ecosystem (Azure Synapse, Azure Data Factory, Power BI).
Advanced SQL (stored procedures, window functions) and Python/PySpark for optimized data processing.
Experience or familiarity with Copilot AI, is highly advantageous.
Architecture & Migration:
Proven track record of architecting and executing migrations from traditional Azure data architectures to Microsoft Fabric.
Demonstrated experience scaling platform performance to support enterprise user bases.
Industry & Domain Experience:
Experience integrating GXP manufacturing and quality data into cloud platforms to support stringent regulatory data streams within the Biotech / Life Sciences sector.
Strong knowledge of modern ETL/ELT pipeline orchestration, data governance, and data lakehouse architectures.
DevOps & Governance:
Deep understanding of SDLC/Agile and Azure DevOps for CI/CD and artifact management.
Knowledge of Azure security best practices (AD, NSG, encryption) and compliance standards.
Certifications Preferred: Azure Data Engineer Associate, Fabric Data Engineer Associate, and Azure Solutions Architect Expert.
Logistics & Shift Overlap:
Full working time overlap with eastern-US-based team hours.
Responsibilities
Platform Migration: Architect and implement the migration of the analytics environment from Azure to Microsoft Fabric.
Regulatory Data Engineering: Integrate GXP manufacturing and quality data streams into the platform to expand capabilities for regulatory compliance.
Quality & Governance: Implement a robust Data Quality Framework using Python and SQL to identify anomalies and ensure data integrity across the Lakehouse and Warehouse layers.
Performance Scaling: Fine-tune and scale platform performance, data pipelines, and capacity settings to ensure optimal responsiveness for over 500 Power BI users. Manage and fine-tune Azure/Fabric resources, including Spark Pools, SKUs, and Capacity settings, to ensure high performance during peak times while maintaining cost-efficiency.
Pipeline Orchestration: Build, maintain, and optimize scalable data integration pipelines using Azure Data Factory, Azure Synapse, and Microsoft Fabric features.
Monitoring & Alerting: Build and enforce proactive monitoring frameworks utilizing Power BI dashboards and Microsoft Teams notifications for real-time failure alerts.
Advanced Capabilities: Leverage Microsoft Fabric tools and AI capabilities, such as Copilot AI, to enhance functionality and operational efficiency.
Cross-Functional Collaboration: Work closely with project leadership and key stakeholders to maintain seamless alignment during US business hours.
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.
