Fabric Analytics Data Engineer

Fabric Analytics Data Engineer 
Hybrid; Newark, NJ
$94k - $145k plus bonus
For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.

Role & Responsibilities Overview:
•    Architect and implement end‑to‑end data solutions using Microsoft Fabric components including Data Factory, Lakehouse, Warehouse, Real‑Time Analytics, and OneLake.
•    Design scalable data models, integration patterns, and storage strategies to support insurance datasets such as policy, claims, billing, actuarial, and customer information.
•    Create architectural blueprints, reference architectures, and reusable frameworks that align with enterprise engineering and cloud standards.
•    Develop and manage ingestion pipelines using Fabric Data Factory, enabling batch, real‑time streaming, and API‑based data integrations.
•    Build Lakehouse‑centered architectures to support advanced analytics, reporting, and machine learning workloads.
•    Optimize data pipelines for performance, reliability, and cost efficiency across Azure and Fabric environments.
 

Candidate Profile:

• 7+ years of experience in data architecture, data engineering, or analytics platform design.
• Strong hands on experience with Microsoft Fabric and related Azure services.
• Deep understanding of insurance data domains (policy, claims, underwriting, actuarial, billing).
• Expertise in data modeling (dimensional, canonical, semantic models).
• Strong knowledge of data governance, metadata management, and data quality practices.
• Proficiency with SQL, Python, and modern data engineering frameworks.
• Excellent communication and stakeholder management skills.
• Experience with Microsoft Purview, Power BI, Databricks, or Azure Synapse.
• Familiarity with modern data architecture concepts (data mesh, data fabric, Lakehouse).
• Certifications such as Azure Data Engineer
• Prior experience in P&C or Life insurance data modernization programs.
• Needs to work from client location in Newark, NJ

• Collaborate with Data Governance teams to ensure adherence to enterprise data standards, lineage tracking, metadata management, and data quality rules.
• Implement governance and compliance capabilities within Fabric, including cataloging, sensitivity labeling, and granular access control.
• Support regulatory requirements for insurance data, ensuring compliance with NAIC guidelines, state-level regulations, and data privacy laws.
• Partner with cloud engineering and security teams to optimize Fabric deployments integrated with Azure AD, Microsoft Purview, and Power BI.
• Ensure architectural alignment with enterprise cloud strategy, security frameworks, and operational guardrails.
• Evaluate new Microsoft Fabric features, capabilities, and roadmap items, recommending adoption and modernization strategies.
• Collaborate with business and analytics stakeholders to translate domain requirements into robust, scalable data solutions.
• Provide technical direction and architectural guidance to data engineers, analysts, and BI developers across projects.
• Lead design reviews and enforce architectural consistency across data initiatives and engineering teams.
• Define and implement Fabric best practices for performance tuning, storage optimization, and cost governance.
• Establish strong data security models, including RBAC, encryption, data masking, and secure access patterns.
• Monitor Fabric platform health and proactively manage risks, ensuring high availability and operational resilience.