Director - Data Analytics & Engineering

MSIG Holdings•Warren, NJ

4d•Hybrid

About The Position

MSIG USA is seeking an experienced and high-caliber Director of Data Analytics & Engineering to lead its data engineering and analytics functions. This senior leadership role is responsible for building, managing, and scaling a high-performing team of data engineers, analytics engineers, and BI developers. The role will deliver the data infrastructure, pipelines, and insights that power the P&C insurance business. Reporting directly to the CDAO, the Director will own the end-to-end delivery of MSIG USA's data engineering platform and analytics capabilities, from raw data ingestion and pipeline orchestration through curated data products, semantic models, and executive-facing dashboards. The role demands a leader who can think strategically, manage and develop talent, and stay technically credible, fostering engineering excellence and a product mindset within the data team. Close collaboration with business leaders in Underwriting, Claims, Actuarial, Finance, Reinsurance, and Product is essential to translate data into measurable business value.

Requirements

Bachelor’s degree in computer science, Data Engineering, Information Systems, or a related technical field.
10+ years of progressive experience in data engineering, analytics, or data platform roles — with at least 4+ years in a people management and leadership capacity.
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 — P&C insurance strongly preferred.
Experience leading BI and analytics delivery at enterprise scale, including Power BI semantic model governance and self-service analytics enablement.

Nice To Haves

Master's degree preferred.

Responsibilities

Lead, manage, and grow a multi-disciplinary team of data engineers, analytics engineers, and BI/reporting developers across MSIG USA's insurance domains.
Recruit top-tier talent, build a strong engineering culture, and develop clear career paths and growth frameworks for data engineering and analytics professionals.
Establish a data-as-a-product mindset across the team — ensuring every data asset is owned, documented, reliable, and fit for purpose.
Set clear goals, performance expectations, and OKRs for the team; conduct regular performance reviews and provide continuous coaching and feedback.
Foster a culture of engineering excellence, accountability, continuous improvement, and collaborative delivery.
Own the design, development, and operations of MSIG USA's data engineering platform built on Microsoft Fabric, Databricks, Azure Data Lake (OneLake), and Azure Data Factory.
Lead the delivery of Medallion architecture (Bronze/Silver/Gold) pipelines across all insurance domains — Policy, Claims, Underwriting, Actuarial, Finance, and Reinsurance.
Oversee development of Delta Live Tables, batch and streaming pipelines, and feature engineering workflows in Databricks and Fabric.
Drive adoption of DataOps practices including CI/CD for data pipelines, automated testing, data contract enforcement, and pipeline observability.
Ensure platform reliability, SLA adherence, and proactive incident management for all production data pipelines and data products.
Partner with the Enterprise Data & AI Architect to implement and evolve the Data Mesh architecture, enabling domain teams to own and publish trusted data products.
Oversee the development and governance of enterprise semantic models, data marts, and dimensional models in Microsoft Fabric and Power BI, serving as the trusted analytics layer for business teams.
Drive adoption of dbt or equivalent transformation frameworks for analytics engineering — ensuring transformation logic is version-controlled, tested, and documented.
Establish and enforce metric definitions, KPI standards, and business glossary alignment across Underwriting, Claims, Actuarial, Finance, and Reinsurance reporting.
Champion self-service analytics — enabling business users to confidently explore data through governed Power BI semantic models without requiring IT intervention.
Own the BI and reporting roadmap for MSIG USA — managing the delivery of executive dashboards, operational scorecards, and domain-specific analytics across all business functions.
Ensure Power BI delivery adheres to enterprise standards for performance, security (RLS/OLS), version control, and deployment pipelines.
Drive reduction in spreadsheet-based reporting and manual data preparation by replacing legacy workflows with governed, automated data products.
Translate complex business requirements from Underwriting, Claims, Actuarial, and Finance into reliable, high-quality BI solutions with clear lineage and documentation.
Define and enforce data quality standards and SLAs across all engineering pipelines and analytics products — partnering with the Data Governance function and Data Product Owners.
Implement data observability frameworks to proactively detect and resolve data freshness, completeness, and accuracy issues before they impact business decisions.
Partner with the Data Governance team to ensure pipelines and data products are cataloged, lineage, and classified in Microsoft Purview.
Ensure all engineering and analytics outputs comply with NAIC, SOC 2, CCPA, and audit requirements relevant to P&C insurance data.
Partner with the AI Engineering team to deliver feature pipelines, training datasets, and model inference infrastructure that support AI and machine learning use cases across the business.
Enable Generative AI and LLM integrations within the data platform — including document ingestion pipelines, vector store management, and structured/unstructured data processing for RAG architectures.
Support the MSIG Nexus intelligence portal with reliable, low-latency data products that power real-time analytics, AI summaries, and self-service reporting.
Identify opportunities to automate manual data workflows using AI-assisted data transformation, anomaly detection, and intelligent pipeline monitoring.
Serve as the primary data engineering and analytics partner to business domain leaders across Underwriting, Claims, Actuarial, Finance, and Reinsurance — translating domain needs into engineered data solutions.
Develop and manage the data engineering and analytics roadmap in alignment with the CDAO's strategic priorities and enterprise data strategy.
Present roadmap progress, delivery status, and platform health metrics to senior leadership and the CDAO on a regular cadence.
Lead vendor relationships and participate in technology evaluations, RFPs, and contract negotiations for data platform tooling and services.
Manage the data engineering and analytics budget — including cloud infrastructure costs, tooling licenses, and contractor spend.