MS Fabric Consultant- Hybrid

Calance; Charlotte (NC); On-site; USD 140,000 - 190,000; Full time

Job summary

Calance seeks a senior data architect/engineer to stand up Microsoft Fabric as the data and AI platform for a multi-unit manufacturing division. You’ll onboard business units with an implementation partner and design patterns for a repeatable model.

You will own ingestion from ERPs, design the layered data model with conformed dimensions, implement deployment pipelines, and govern the platform end-to-end to support analytics and AI initiatives.

Qualifications

• Experience building a Fabric or lakehouse from scratch.
• Ability to justify capacity sizing with numbers.
• Ability to write production SQL, Python, and Spark code.
• Comfort working with non-technical stakeholders.
• Knowledge of governance vs bureaucracy.

Responsibilities

• Ingest data from multiple ERPs and LOB systems.
• Design layered data models and conformed dimensions.
• Semantic modeling for reporting and AI tooling.
• Implement deployment pipelines, orchestration, and monitoring.
• Build the initial pattern to enable repeatability.

Skills

SQL

Python

Spark

Job description

Context

Client is standing up Microsoft Fabric as the data and AI platform for a multi-business-unit manufacturing segment. The platform decision is made; the foundation is not yet built. There is no existing internal data team you are the first. You will work directly with the VP of Digital & AI and alongside an implementation partner, onboarding business units sequentially and turning the first one into a repeatable pattern.

The architecture and governance third

• Tenant, domain, and workspace design for a segment with several operating business units
• Capacity sizing, cost modelling, and attributing consumption back to business units
• Access, security, and lifecycle model across development, test, and production
• Standards for where metrics are defined, who may certify them, and how a newly acquired company is onboarded
• Being the person who says no when a shortcut would cost us later and who knows which shortcuts are fine

The engineering two-thirds

• Building ingestion from multiple ERPs and line-of-business systems
• Designing and building the layered data model, and the shared conformed dimensions every business unit consumes
• Semantic modelling the certified definitions that reporting and AI tooling read from
• Deployment pipelines, orchestration, monitoring, and the operational discipline to keep it running
• Doing the first build yourself so the pattern is right before anyone repeats it

What we are looking for

• You have built a Fabric or comparable lakehouse environment from nothing, and you have lived with the consequences of your own design decisions
• You can defend a capacity sizing decision with numbers, and say what you would do differently a second time
• You write production code SQL certainly, Python and Spark as needed and have done so recently
• You are comfortable being the only data person in the room with non-technical stakeholders
• You have a view on where governance earns its keep and where it becomes bureaucracy

What this role is not

• Not a pure architect role. If you have not built anything in three years, this will not suit you.
• Not a pure engineering role. You will be making and defending decisions, not implementing someone else’s design.
• Not a role where you inherit a team. You establish the practice; others join later.
• Not a greenfield-with-unlimited-budget role.