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Fusion Academy · 19 hours ago

Senior Data Engineer – Data and Analytics (Remote)

United States

Full-time

Remote

Senior Level

5+ years exp

Fusion Education Group is seeking a Senior Data Engineer to lead data and analytics architecture for their data-aware organization. In this role, you will oversee the design, development, and implementation of data solutions while mentoring a small team, ensuring that the data infrastructure supports advanced analytics and business intelligence across the organization.

Primary/Secondary Education

Culture & Values

Responsibilities

Design, architect and operate modern data platforms on Azure

Architect and maintain data lakes/lakehouses with Azure Data Lake Storage (ADLS) and Databricks

Establish robust ELT patterns using Azure Data Factory (ADF) pipelines with a focus on cost, performance, and reliability

Lead the full lifecycle—from prototyping to production deployment, including pipelines, APIs, front/back-end integration, monitoring, and maintenance

Design scalable, reliable systems; optimize performance, latency, cost, and integrate telemetry for iterative improvement

Build intelligent data products using Azure AI

Productionize ML workflows in Azure Machine Learning (workspaces, model registry, endpoints

Integrate Azure Cognitive Services (Language, Vision, Speech) and Azure OpenAI Service for enrichment, classification, summarization, and retrieval-augmented generation (RAG)

Orchestrate LLM applications using Azure ML pipelines, implementing guardrails, prompt versioning, and telemetry

Deliver low-latency feature stores and micro-batch ingestion for ML and BI workloads

Data modeling, quality, and observability

Define canonical and dimensional models; enforce standards (naming, lineage, SCD patterns) across marts and semantic layers (e.g., Power BI/Fabric)

Security, compliance, and governance (MCP best practices)

Apply Azure RBAC, Managed Identities, Private Endpoints, Key Vault, and Customer-Managed Keys; enforce policy with Azure Policy and Defender for Cloud

Performance, reliability, and FinOps

Tune Databricks compute, caching, partitioning, Z-order, and query plans; optimize storage tiers and autoscaling

Monitor SLOs/SLIs with Azure Monitor, Log Analytics, and custom metrics; build cost dashboards and alerts for proactive FinOps

Collaboration, enablement, and leadership

Partner with business units on projects to define scope and deliverables; enable self-service via curated datasets and semantic models

Mentor engineers on Microsoft stack best practices; contribute to standards, templates, and reusable components aligned with Microsoft certifications (e.g., Azure Data Engineer, Azure AI Engineer)

Qualification

Azure Data LakeDatabricksAzure Data FactoryMachine LearningPythonAPI DevelopmentData ModelingAzure AI ServicesDevOps PracticesVersion ControlCommunication SkillsCollaboration SkillsMentorship

Required

Bachelor's or Master's degree in Computer Science, Engineering, or related field

5+ years of experience in data engineering or AI/ML production systems

Advanced proficiency in Databricks and at least one programming language (Python, Scala, or Java)

Knowledge in implementing, fine-tuning, and deploying LLMs

Strong capabilities in API development, version control, unit testing, and documentation

Microsoft Certified: Azure Data Engineer Associate (DP-203) and/or Azure AI Engineer Associate (AI-102) strongly preferred; MCP/MCSA/MCSE or equivalent legacy Microsoft certifications a plus

Hands-on experience with modern data pipeline orchestration tools (Azure Data Factory)

Deep knowledge of Azure data and AI services (Azure Data Lake, Azure Machine Learning, Azure Cognitive Services, Azure OpenAI)

Strong understanding of data modeling, warehousing, and data lake architecture

Experience with DevOps practices and version control (Azure DevOps, Git, CI/CD)

Excellent communication and collaboration skills

Microsoft Certified Professional (MCP) or relevant Azure certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate) are highly preferred

Mentor Data Analytics Team members with best practices in the data space

Current with industry trends in data engineering, Azure AI, and cloud platforms

Preferred

Experience deploying machine learning models to production using Azure ML

Exposure to real-time data streaming (Azure Event Hubs, Kafka)

Exposure to Model Context Protocol (MCP) and AI agents

Benefits

Medical, dental, and vision plans

An opportunity to contribute to a Health Savings Account (HSA)

Tax-advantaged commuter benefits

Employee assistance program

Sick time, paid holidays and vacation in accordance with company policy and state law

Accident and life insurance as well as short- and long-term disability

401(k) plan with company match, based on eligibility

This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy.