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Fabric Data Engineer — Workplace Engineering

Job in Lancaster, Lancaster County, Pennsylvania, 17622, USA
Listing for: SwiftCruit
Full Time position
Listed on 2026-07-19
Job specializations:
  • Software Development
    Data Engineering
Salary/Wage Range or Industry Benchmark: 130000 - 190000 USD Yearly USD 130000.00 190000.00 YEAR
Job Description & How to Apply Below

About the Role

Vanguard is standing up Microsoft Fabric as the enterprise data and analytics foundation that powers our Workplace AI, Power BI, and cross-cloud analytics estate. We are partnering with Microsoft on a CDAO‑led Fabric Enablement engagement and are building this capability on an F256 Reserved capacity, integrated with the broader Vanguard data, identity, and security stack — including One Lake Direct Lake against AWS S3, Entra  Okta federation, and Microsoft Purview.

Role

Summary

We are hiring a hands‑on Fabric Data Engineer to own the data layer of that capability. This is a builder's role, not an architect‑only role. The engineer designs and implements scalable data products in One Lake — lake houses, warehouses, pipelines, notebooks, semantic‑model‑ready Delta tables — and is accountable for the lifecycle, governance, and operational health of the Fabric platform. The complementary AI Engineer role consumes that foundation to build agents, copilots, and Foundry orchestrations;

this engineer makes sure the data underneath is governed, monitored, and ready.

You will partner closely with the AI Engineer on AI‑ready data products and semantic‑layer handoffs; with our Technical Project Manager on program delivery, enablement, and change management; and with our Cloud Domain Architect on platform alignment. You will work alongside the Microsoft CDAO Fabric Enablement team and Vanguard partners across CDAO and Workplace Engineering. You will be a core member of the emerging Workplace AI Fusion Team.

This is a strategic engineering and implementation role, not a support position.

Key Responsibilities
  • Design and implement scalable data storage in One Lake using Lake houses (Delta) and Warehouses (T‑SQL); choose the right item for each workload and configure SQL analytics endpoints, shortcuts, and One Lake security.
  • Build and maintain Spark notebooks (PySpark), Data Factory pipelines, Dataflows Gen2, Copy Jobs, and mirroring for batch and incremental ingestion at enterprise scale.
  • Build Real‑Time Intelligence solutions:
    Event streams, Event houses / KQL databases, Activator reflexes, and Spark structured streaming for low‑latency workloads.
  • Optimize Lakehouse tables (OPTIMIZE, V‑Order, Z‑Order, partitioning) and Direct Lake semantic‑model‑ready datasets so downstream Power BI and AI agents perform predictably.
ALM & Lifecycle Engineering
  • Implement source control, branching, and CI/CD using native Fabric Git integration (Azure Dev Ops and Git Hub), Fabric Deployment Pipelines, and the Microsoft fabric‑cicd Python library.
  • Automate Dev / Test / Prod promotion against the Fabric REST API using service principals and Workload Identity Federation; codify environment‑aware bindings via Variable Libraries and parameter.yml.
  • Operate a Feature → Dev → UAT → Prod branching pattern — native Git on Feature and Dev work spaces, pipeline‑pushed promotion to UAT and Prod — with mandatory PR review, cherry‑pick promotion, and one repo per team to scope blast radius.
  • Own the lifecycle of Fabric data components from creation through retirement, ensuring every environment is reproducible from the Git Hub pipeline rather than from the Fabric UI.
Platform Operations & Monitoring
  • Operate the Fabric F256 capacity: monitor CU consumption with the Capacity Metrics App, manage smoothing windows, diagnose interactive and background throttling, and right‑size workloads.
  • Build telemetry using the Monitoring Hub, per‑workspace Workspace Monitoring (Eventhouse‑based KQL logs), Eventhouse monitoring, and the Admin Monitoring Workspace to surface refresh failures, pipeline errors, and semantic‑model health.
  • Define dashboards and alerts for ingestion, transformation, refresh, and capacity health; drive root‑cause analysis on production incidents and feed lessons back into platform standards.
  • Define and operate the on‑call model for production data pipelines and Fabric items in partnership with Tier 3 Engineering.
Standards, Governance & Security
  • Define and enforce Fabric platform standards through Terraform‑based IaC using the official microsoft/fabric provider (work spaces, capacities, domains, items), workspace templates, naming and…
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