Lead Data Engineer

About Fusemachines Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, our core mission is to democratize AI. We have a presence in 4 countries – Nepal, United States, Canada, and the Dominican Republic – and more than 400 full-time employees. Fusemachines seeks to bring its global expertise in AI to transform companies around the world. About the Role Location : Remote (Full-time) This full-time position is responsible for designing, building, maintaining, and optimizing the infrastructure required for data integration (batch and real-time), storage (including databases and data modeling), processing, and analytics (BI, visualization, and advanced analytics) using Microsoft Azure in the public sector. The Lead Data Engineer works closely with cross-functional teams to support business objectives and serves as an Azure Cloud solutions subject-matter expert (SME), collaborating with the Delivery team on solution design and implementation. This role is split approximately between hands‑on data engineering (building pipelines, modeling data, troubleshooting) and solution architecture (designing the platform, setting standards, and leading technical direction). Responsibilities Lead the design and implementation of end‑to‑end data solutions on Azure, architecting data pipelines and data models; troubleshoot and optimize pipelines; set platform standards and provide technical leadership; collaborate with cross‑function teams on solution design; act as Azure Cloud SME. Qualifications & Experience Bachelor's degree in Computer Science, Information Systems, or a related field. Minimum 5+ years as a Data & Analytics Solution Architect or Senior / Lead Data Engineer with strong hands‑on experience in Microsoft Azure environments. 5+ years working with Azure Cloud Platform and Azure DevOps (exposure to AWS / GCP is a plus). Proven experience delivering end‑to‑end data and analytics projects, including hands‑on development as a Senior or Lead Data Engineer. Deep and recent experience with Microsoft Fabric, Azure Databricks, Azure Functions, and PySpark for real‑time and low‑latency data pipeline design. Expertise in data modeling, integration (ETL / ELT), warehousing, and BI using services such as Data Factory, Data Lake, Stream Analytics, and Azure SQL Database. Experience designing and implementing GraphQL and RESTful APIs within Azure ecosystems. Preferred Certifications Microsoft Certified : Azure Fundamentals Microsoft Certified : Azure Data Engineer Associate Microsoft Certified : Azure Solutions Architect Expert Microsoft Certified : Azure AI Engineer Associate Required Skills & Competencies Deep experience designing and implementing end‑to‑end data and analytics solutions using Microsoft Azure services such as Microsoft Fabric, Azure Databricks, Azure Data Factory, Azure Data Lake, Azure Stream Analytics, Azure SQL Database, and Power BI. Proven hands‑on experience building and optimizing real‑time, low‑latency pipelines using PySpark, Azure Functions, Event Hubs, and Stream Analytics. Strong understanding of CI / CD, Infrastructure as Code (Terraform or ARM templates), configuration management, automated testing, and cost‑optimization principles. Expertise in data modeling, data integration (ETL / ELT), warehousing, BI, and advanced analytics (ML / AI) within Azure environments, ensuring scalable and resilient designs. Proficiency in Python and SQL, with ability to diagnose performance issues, optimize pipelines, and ensure system reliability. Experience designing data governance, cataloging, data quality, and lineage frameworks; implementing Azure security best practices (IAM, encryption, compliance); and managing monitoring tools such as Azure Monitor, Application Insights, or Datadog. Familiarity with Kubernetes and Docker for scalable architecture, including design and configuration of containerized services. Strong ability to work cross‑functionally with architects, engineers, and data scientists, and to clearly document architecture and deployment configurations. Committed to staying updated with emerging Azure technologies, AI / ML integrations, and data architecture best practices to drive innovation and efficiency. Equal Opportunity Employer Fusemachines is committed to fostering a diverse and inclusive workplace. We welcome applications from all qualified individuals regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, protected veteran status, or any other legally protected status. Referrals Referrals increase your chances of interviewing at Fusemachines by 2x. #J-18808-Ljbffr