Senior Data Engineer​/Tech Lead

Position: Senior Data Engineer/ Tech Lead
About Fusemachines

Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients' AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI.

Fusemachines serves companies in industries such as retail, manufacturing, and government.

Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI

About

The Role

This is a full-time, remote position for a high-impact Technical Lead and Senior Data Engineer. You will lead the modernization of legacy on-premises systems into a cutting-edge, cloud-native architecture.

As a Technical Lead, your primary goal is to serve as the backbone of our engineering excellence—training, mentoring, and coaching the rest of the team on Azure best practices and Microsoft Fabric implementation. You will oversee the transition from monolithic SQL Server 2012 environments to a sophisticated hybrid platform utilizing Microsoft Fabric, ensuring 100% audit traceability and real-time data synchronization for critical public programs.

Qualification / Skill Set Requirement:

Experience:

5+ years of hands-on data engineering experience with deep expertise in the Azure ecosystem
Microsoft Fabric Expertise:
Proven experience with Microsoft Fabric, specifically Event streams, Lake houses (Delta over Blob/Data Lake Storage), Fabric Notebooks, Data Factory, and GraphQL
Data Integration & Streaming:
Deep knowledge of Change Data Capture (CDC) and Transaction Replication from on-premises SQL Server 2012 to the cloud
Expertise in Spark Streaming and PySpark for real-time data processing
Technical Architecture:
Hands-on experience with Graph

QL in Fabric and Azure Functions (acting as proxies/API bridges)
Proficiency in Azure API Management (APIM) for governing secure interfaces and managing throttling/quotas
Experience integrating complex third-party platforms like Salesforce and low-code/no-code applications via API-led connectivity
Development

Skills:

Advanced SQL (stored procedures, window functions) and Python/PySpark for optimized data processing
Strong background in ETL/ELT orchestration using Azure Data Factory and Airflow
Strong experience with PowerBI
Dev Ops & Governance:
Deep understanding of SDLC/Agile and Azure Dev Ops for CI/CD and artifact management
Knowledge of Azure security best practices (AD, NSG, encryption) and government compliance standards
Certifications Preferred:
Azure Data Engineer Associate, Fabric Data Engineer Associate, and Azure Solutions Architect Expert

Responsibilities

Technical Leadership:
Serve as the Lead Engineer to design and implement scalable, hybrid data solutions that bridge legacy on-premises databases with modern Azure cloud-native layers
Mentorship &

Coaching:

Actively train and mentor junior engineers, fostering a culture of technical excellence and ensuring the team adheres to Azure and Fabric best practices
Real-Time Engineering:
Develop and maintain Event-Driven architectures using CDC and Spark Streaming to achieve sub-2-second data propagation for time-sensitive financial reporting
Pipeline Optimization:
Architect Incremental Data Sync (Delta-based) workflows to replace high-latency full refreshes, significantly reducing operational risk and API usage
API Management:
Design and govern a Graph

QL Access Layer and Azure Functions to mask legacy system limitations and provide conditioned, validated data to frontend applications
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
Infrastructure Management:
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
Monitoring & Alerting:
Build and enforce proactive monitoring frameworks utilizing Power BI dashboards and Microsoft Teams notifications for real-time failure alerts

Collaboration:

Work closely with cross-functional stakeholders and third-party vendors to align API contracts and business logic for seamless integration with Salesforce or other applications

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.

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