Director - Data Analytics and Engineering

MSIG USA•Warren Township, NJ

3d•$180,000 - $200,000

About The Position

MSIG USA is seeking a senior leader to direct its data engineering and analytics functions. The role builds, manages, and scales a team of data engineers, analytics engineers, and BI developers to deliver data infrastructure, pipelines, and insights for the company’s property and casualty insurance business. Reporting directly to the CDAO, the Director owns end-to-end delivery of the data engineering platform and analytics capabilities, from data ingestion and orchestration through curated data products, semantic models, and executive dashboards. The role sets technical and organizational direction, promotes a product mindset and engineering excellence, and partners with business leaders across Underwriting, Claims, Actuarial, Finance, Reinsurance, and Product to deliver measurable business value. The position oversees the Microsoft Fabric, Databricks, Azure Data Lake (OneLake), and Azure Data Factory platform; enterprise data pipelines and analytics models; BI and reporting; data quality, governance, and observability; and data capabilities that enable AI and advanced analytics. The Director also develops the roadmap, manages vendor relationships and budgets, and reports progress and platform health to senior leadership and the CDAO.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
At least 10 years of progressive experience in data engineering, analytics, or data platform roles.
At least 4 years of experience in people management and leadership.
Proven track record of building and scaling data engineering teams in complex, multi-domain enterprise environments.
Demonstrated experience delivering production-grade data platforms on Microsoft Azure, with strong hands-on depth in Databricks and Microsoft Fabric.
Significant experience in financial services, insurance, or regulated industries.
Experience leading enterprise-scale BI and analytics delivery, including Power BI semantic model governance and self-service analytics enablement.

Nice To Haves

Master’s degree.
P&C insurance experience.

Responsibilities

Lead, manage, and grow a multidisciplinary team of data engineers, analytics engineers, and BI/reporting developers across insurance domains.
Recruit talent, develop career paths and growth frameworks, set team goals and OKRs, conduct performance reviews, and provide coaching and feedback.
Build an engineering culture focused on accountability, continuous improvement, collaboration, and a data-as-a-product mindset.
Own the design, development, and operation of the data engineering platform built on Microsoft Fabric, Databricks, Azure Data Lake (OneLake), and Azure Data Factory.
Lead delivery of Bronze, Silver, and Gold Medallion architecture pipelines across Policy, Claims, Underwriting, Actuarial, Finance, and Reinsurance.
Oversee Delta Live Tables, batch and streaming pipelines, and feature engineering workflows in Databricks and Fabric.
Drive DataOps practices, including CI/CD, automated testing, data contract enforcement, and pipeline observability.
Ensure production pipeline and data product reliability, SLA adherence, and proactive incident management.
Partner with the Enterprise Data & AI Architect to implement and evolve Data Mesh architecture and enable domain teams to own and publish trusted data products.
Oversee enterprise semantic models, data marts, and dimensional models in Microsoft Fabric and Power BI.
Promote dbt or equivalent transformation frameworks and ensure transformation logic is version-controlled, tested, and documented.
Establish metric definitions, KPI standards, and business glossary alignment across business domains.
Promote governed self-service analytics through Power BI semantic models.
Own the BI and reporting roadmap, including executive dashboards, operational scorecards, and domain analytics.
Ensure Power BI delivery meets enterprise standards for performance, security (RLS/OLS), version control, and deployment pipelines.
Replace spreadsheet-based reporting and manual data preparation with governed, automated data products.
Translate business requirements into reliable BI solutions with clear lineage and documentation.
Define and enforce data quality standards and SLAs in partnership with Data Governance and Data Product Owners.
Implement data observability to detect and resolve freshness, completeness, and accuracy issues.
Partner with Data Governance to catalog, lineage-track, and classify pipelines and data products in Microsoft Purview.
Ensure engineering and analytics outputs comply with relevant NAIC, SOC 2, CCPA, and audit requirements.
Partner with AI Engineering to deliver feature pipelines, training datasets, and model inference infrastructure for AI and machine learning use cases.
Enable Generative AI and LLM integrations, including document ingestion, vector store management, and data processing for RAG architectures.
Support the MSIG Nexus intelligence portal with reliable, low-latency data products for real-time analytics, AI summaries, and self-service reporting.
Identify opportunities to automate manual data workflows using AI-assisted transformation, anomaly detection, and intelligent pipeline monitoring.
Serve as the primary data engineering and analytics partner to business domain leaders and translate their needs into engineered solutions.
Develop and manage the data engineering and analytics roadmap in alignment with the CDAO’s priorities and enterprise data strategy.
Present roadmap progress, delivery status, and platform health metrics to senior leadership and the CDAO.
Lead vendor relationships and participate in technology evaluations, RFPs, and contract negotiations.
Manage the data engineering and analytics budget, including cloud infrastructure, tooling licenses, and contractor spending.