Microsoft Fabric Data Engineer

2020 Companies•Atlanta, GA

1d•Onsite

About The Position

This role involves building the engine behind client revenue by developing and maintaining the Microsoft Fabric platform, which is the backbone of a growing Analytics & BI practice. The engineered dashboards drive executive decisions, surface revenue opportunities, and set client standards. The engineer will optimize pipelines and redesign semantic models, with a direct impact on renewal conversations and client satisfaction scores. The company is scaling fast and seeks an engineer who thinks in systems, communicates with clarity, and treats client SLAs as non-negotiable.

Requirements

2–5 years of data engineering experience
Strong SQL, data modeling, and hands-on Delta Lake experience
Microsoft Fabric experience – you’ve built it, not just read about it
Dimensional modeling you can defend in a design review
Power BI semantic model optimization experience
Experience building scalable ingestion frameworks
A track record in client-facing or revenue-driven analytics environments
Uses critical thinking to break down ambiguous problems, evaluates tradeoffs, and makes sound, data-informed decisions that balance performance, scalability, and business impact
Strong collaboration and teamwork skills, exceptional communication skills, written and verbal, that translate complex technical decisions for non-technical audiences
Experience working in agile environments using features and user stories
A growth mindset — you're energized by hard problems, not slowed down by them, strong team player

Nice To Haves

dbt experience
GitHub-based development workflows and CI/CD experience
Agile mindset and development experience

Responsibilities

Build Scalable Client Data Pipelines for scale from day one
Develop and maintain high-quality, reliable Microsoft Fabric pipelines and notebooks that directly support analytics and reporting
Implement incremental loads, watermarking, and merging logic
Design ingestion patterns that support rapid onboarding of new clients
Engineer monitoring and observability to prevent SLA breaches while catching problems before clients do
Ensure data quality and reliability across datasets
Implement Medallion architecture (Bronze/Silver/Gold)
Design and implement dimensional models for revenue-focused analytics that meet reporting and analytics needs
Design reusable, scalable data structures across multiple clients
Design data structures that don’t become someone else’s technical debt
Optimize partitioning and storage for predictable performance
Maintain consistency and usability across datasets
Improve Direct Lake and semantic model performance in Power BI
Reduce refresh times and memory usage
Partner with BI developers to maintain high modeling standards
Monitor Fabric capacity usage and workload patterns
Optimize refresh strategies and reduce compute spikes
Contribute to GitHub workflow and future dbt integration roadmap
Collaborate closely with BI developers, analysts, and stakeholders
Translate requirements into well-defined features and user stories
Participate actively in agile ceremonies
Explain technical decisions, obtain prioritization and approval before execution
Do light documentation to build institutional memory
Follow SDLC practices, including Git, CI/CD, and code reviews
Deliver work iteratively with high quality and predictability
Ship frequently in small batch sizes