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About the Role

Lead the Data and AI architecture and engineering function as a technical manager, owning Microsoft Fabric architecture, enterprise data and semantic modeling, integration design, and governed AI enablement while building an engaged, capable, and accountable team.

Responsibilities

Clearly define and communicate team roles, expectations, and responsibilities.
Provide coaching, guidance, and support to help employees achieve performance and development goals.
Deliver consistent, constructive, feedback to recognize achievements, address challenges, and reinforce desired behaviors.
Conduct regular 1:1 meeting and ensure timely completion of performance review cycles, maintaining alignment and accountability.
Hold staff accountable for compliance with organizational policies and standards.
Foster a culture of continuous learning, innovation, and accountability by encouraging team members to pursue new challenges and opportunities.
Model and reinforce organizational values, actively recognizing and celebrating behaviors that exemplify them.
Own the end-to-end Microsoft Fabric reference architecture across OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, notebooks, Real-Time Intelligence, Power BI, workspaces, domains, and capacities.
Lead the team delivering foundational Fabric patterns and priority platform components; stay hands-on for high-risk design, prototyping, review, and troubleshooting.
Define medallion, batch, CDC, streaming, mirroring, shortcut, deployment, security, monitoring, and capacity-management patterns.
Maintain current architecture diagrams, standards, roadmaps, architecture decisions, and implementation guardrails.
Own conceptual, logical, physical, canonical, dimensional, and enterprise semantic model standards across policy, claims, provider, patient safety, underwriting, actuarial, and finance domains.
Establish Power BI semantic model standards for measures, calculation groups, naming, certified datasets, reuse, refresh, performance, lineage, ownership, and RLS/OLS/CLS.
Define data contracts, model versioning, metadata, glossary, master/reference data, ontology, and knowledge-graph alignment.
Design secure integrations across Fabric, Azure, operational systems, content platforms, and external providers using APIs, events, CDC, streaming, files, and batch patterns.
Establish Git-based delivery, pull-request review, automated testing, CI/CD, environment promotion, release, rollback, observability, incident response, and operational-readiness standards.
Define service objectives and telemetry for pipelines, capacities, semantic models, AI services, and critical data products; lead root-cause analysis and durable remediation without blame.
Embed least privilege, secrets management, PHI/PII controls, sensitivity, retention, data quality, lineage, auditability, and responsible AI controls into delivery patterns.
Forecast, monitor, explain, and optimize platform capacity, compute, storage, licensing, and vendor cost against business value.
Translate strategy and ambiguous business needs into decision-ready options, recommendations, diagrams, roadmaps, staffing plans, and executable work for technical and executive audiences.
Partner with Enterprise Architecture, Security, Infrastructure, Governance, Claims, Underwriting, Actuarial, Reporting, Legal/Compliance, Finance, and vendors to resolve tradeoffs and dependencies.
Communicate risks early with context, impact, options, and a recommended action; represent decisions with composure, transparency, and sound judgment.
Lead adoption of architecture standards and new ways of working through stakeholder engagement, education, measurement, and reinforcement.
Maintain full compliance with all organizational policies, procedures, and established standards.
Keep technical knowledge and skills current to effectively support department priorities.
Complete all performance and development activities – including the performance review process – in a timely manner.
Fulfill all required training and development obligations to maintain essential skills and credentials.
Complete all mandator compliance courses on time, meeting corporate training standards.
Pursue additional learning opportunities that strengthen professional capabilities and contribute to team and organizational performance, with prior manager approval.

Requirements

Bachelor's or master's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field; equivalent experience considered.
10+ years of deep enterprise data, analytics, engineering, or architecture experience with accountability for architecture decisions in production.
3+ years directly managing and supervising data engineers, analytics engineers, architects, or similar technical staff, including managing a team through change.
Direct accountability for hiring, onboarding, goal setting, performance reviews, coaching, career development, workload planning, succession planning, employee relations, and retention.
Constructive, solution-oriented leadership and strong executive communication.
Regulated-industry experience (insurance, healthcare, or financial services) preferred.

Skills

Microsoft Fabric (OneLake, Lakehouse, Warehouse, Pipelines, Dataflows Gen2, notebooks, Real-Time Intelligence, Power BI, workspaces, security, and capacity governance)
Enterprise data and semantic modeling: conceptual, logical, physical, dimensional, and canonical models; data contracts; Power BI semantic models; lineage; RLS/OLS/CLS; and performance tuning.
SQL
Python
PySpark
Delta Lake
Batch processing
Change Data Capture (CDC)
Streaming data processing
API development
DataOps
Automated testing
Continuous Integration/Continuous Deployment (CI/CD)
Observability
Cost management
Microsoft Fabric architecture
Medallion architecture
Mirroring
Shortcuts
Deployment strategies
Security protocols
Monitoring systems
Capacity management
Conceptual data modeling
Logical data modeling
Physical data modeling
Canonical data modeling
Dimensional data modeling
Enterprise semantic modeling
Power BI semantic models
Measures
Calculation groups
Naming conventions
Certified datasets
Dataset reuse
Data refresh strategies
Performance optimization
Data lineage tracking
Data ownership
Row-Level Security (RLS)
Object-Level Security (OLS)
Column-Level Security (CLS)
Data contracts
Model versioning
Metadata management
Data glossary creation
Master data management
Reference data management
Ontology development
Knowledge graph alignment
Secure integration design
Azure services integration
Operational systems integration
Content platforms integration
External provider integration
Event-driven architecture
File-based data transfer
Batch data transfer
Git-based delivery workflows
Pull-request reviews
Automated testing frameworks
CI/CD pipelines
Environment promotion strategies
Release management
Rollback procedures
Observability tools
Incident response planning
Operational readiness assessment
Service level objectives (SLO) definition
Telemetry implementation
Root-cause analysis
Durable remediation strategies
Least privilege access control
Secrets management
Protected Health Information (PHI) controls
Personally Identifiable Information (PII) controls
Data sensitivity classification
Data retention policy implementation
Data quality assurance
Auditability controls
Responsible AI implementation
Platform capacity forecasting
Compute resource monitoring
Storage resource monitoring
Licensing management
Vendor cost optimization
Business value alignment
Strategic planning
Business needs translation
Decision-ready option development
Recommendation formulation
Diagram creation
Roadmap development
Staffing plan creation
Work execution planning
Technical audience communication
Executive audience communication
Enterprise Architecture collaboration
Security team collaboration
Infrastructure team collaboration
Governance team collaboration
Claims department collaboration
Underwriting department collaboration
Actuarial department collaboration
Reporting department collaboration
Legal/Compliance department collaboration
Finance department collaboration
Vendor management
Tradeoff resolution
Dependency management
Risk communication
Impact assessment
Option analysis
Action recommendation
Decision representation
Composure
Transparency
Sound judgment
Architecture standards adoption
New ways of working implementation
Stakeholder engagement
Educational initiatives
Performance measurement
Behavioral reinforcement
Organizational policy compliance
Procedure adherence
Established standard adherence
Time recording accuracy
Paid time off (PTO) submission
Mandatory corporate training completion
Technical knowledge maintenance
Skill currency maintenance
Department priority support
Performance activity completion
Development activity completion
Performance review process completion
Training obligation fulfillment
Credential maintenance
Compliance course completion
Corporate training standard adherence
Learning opportunity pursuit
Professional capability enhancement
Team performance contribution
Organizational performance contribution
Manager approval for learning opportunities

Location

New York City
Any other TDC Group or ProAssurance office location

Work Type

Hybrid

Experience Level

10+ years of deep enterprise data, analytics, engineering, or architecture experience
3+ years directly managing and supervising data engineers, analytics engineers, architects, or similar technical staff

Education Level

Bachelor's or master's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field; equivalent experience considered.

Salary/Compensations

$124,548 - $163,879
This position is eligible for participation in the Company's Short-Term Incentive Plan (STIP), offering additional compensation driven by individual and company performance.
Compensation is determined based on factors such as skills, experience, education, and market considerations.
Salary may also include additional geographic differential for employees working in higher-cost labor markets, including states such as New York and California.

Benefits

Medical leave
Family leave
Bereavement leave
Same-sex domestic partner benefits
Short-term disability programs
Long-term disability programs
Employee assistance program
Health insurance
Dental insurance
Vision insurance
Health care tax-free spending accounts with a company match
401(k) with company match
Roth IRA with company match
Catch-up plans for 401(k) and Roth IRA
Vacation days
Sick days
Paid personal days
Paid holidays
Life insurance
Travel insurance
Tax-free commuter benefits
In-person learning opportunities
Online learning opportunities
Cross-function career opportunities
Business casual work environment
Time off to volunteer
Matching donations to qualifying nonprofit organizations
Company-sponsored participation at non-profit events

About the Company

The Doctors Company is the nation’s largest physician-owned medical malpractice insurer.
Founded and led by physicians, we are committed to advancing, protecting, and rewarding the practice of good medicine.
The Doctors Company is proud to be Certified™ by Great Place to Work®.