Director - Data Analytics and Engineering

MSIG Holdings•Warren, NJ

About The Position

MSIG USA is seeking an experienced Director of Data Analytics & Engineering to lead and scale its data engineering and analytics functions. This senior leadership role manages a multidisciplinary team of data engineers, analytics engineers, and BI developers, delivering the data infrastructure, pipelines, curated data products, semantic models, and dashboards that support 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. The role sets technical direction, promotes engineering excellence and a data-as-a-product mindset, and partners with business leaders across Underwriting, Claims, Actuarial, Finance, Reinsurance, and Product to turn data into business value. The platform is built on Microsoft Fabric, Databricks, Azure Data Lake (OneLake), and Azure Data Factory. The Director oversees data pipelines and products across insurance domains, semantic models and Power BI reporting, data quality and governance, and data infrastructure supporting AI and machine learning. The role also manages the roadmap, vendor relationships, budget, team development, and communications with senior leadership.

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 in people management and leadership.
Proven record of building and scaling data engineering teams in complex, multi-domain enterprise environments.
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.
Experience in P&C insurance.

Responsibilities

Lead, manage, and grow a multidisciplinary team of data engineers, analytics engineers, and BI/reporting developers.
Recruit talent, establish engineering culture, and develop career paths and growth frameworks for team members.
Promote a data-as-a-product mindset, ensuring data assets are owned, documented, reliable, and fit for purpose.
Set team goals, expectations, and OKRs; conduct performance reviews and provide coaching and feedback.
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/Gold Medallion architecture pipelines across Policy, Claims, Underwriting, Actuarial, Finance, and Reinsurance domains.
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.
Maintain platform reliability, SLA adherence, and proactive incident management for production pipelines and data products.
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 reporting domains.
Enable governed self-service analytics through Power BI semantic models.
Own the BI and reporting roadmap, including executive dashboards, operational scorecards, and domain-specific analytics.
Ensure Power BI delivery meets standards for performance, security, version control, and deployment pipelines.
Replace spreadsheet-based reporting and manual data preparation with governed, automated data products.
Translate business requirements into 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 identify and resolve freshness, completeness, and accuracy issues.
Ensure pipelines and data products are cataloged, lineaged, and classified 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 structured and unstructured 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 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 data 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 spend.