Data and Analytics Engineering Lead, Reinsurance

Marsh McLennan•Norwalk, CT

1d•Hybrid

About The Position

As Data and Analytics Engineering Lead within the Reinsurance Data and Analytics team, you will be instrumental in designing, developing, and deploying enterprise-scale Analytics solutions that enable data-driven decision-making across the organization. You will collaborate with cross-functional teams to architect scalable, secure, and high-performance analytic environments, ensuring alignment with business needs and data governance standards.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering or a related field.
5+ years of experience working within the reinsurance domain, understanding its data and reporting needs.
10+ years of experience in data analytics, with extensive experience delivering enhanced data and analytical capabilities.
Proven expertise in designing and implementing enterprise Power BI solutions, including data modeling, DAX, Power Query, and visualization best practices.
Strong knowledge of cloud data platforms such as Azure Data Lake, Azure Synapse Analytics, Databricks, DBT and integration with Power BI.
Familiarity with data governance, security, and compliance standards related to enterprise reporting.
Excellent problem-solving skills and the ability to troubleshoot complex data issues.
Strong communication skills and the ability to collaborate effectively with cross-functional teams.

Nice To Haves

Proficiency in DAX, Power BI Service, Power BI Embedded, and Power BI REST APIs.
Leveraging AI to enabling Ad Hoc and Self Serve BI capabilities
Knowledge of Python, R, or other scripting languages to enhance Power BI capabilities.
Understanding of information security, data privacy, and cloud security best practices.
Strong communication skills to collaborate with technical and non-technical stakeholders.

Responsibilities

Lead the design and implementation of enterprise BI architecture, including data models, dashboards, reports, and data gateways, ensuring optimal performance, usability, and security.
Collaborate with data engineers, analysts, and stakeholders to translate business requirements into scalable BI solutions, including data modeling, DAX calculations, and visualization best practices.
Ensure adherence to data governance and compliance standards in data modeling and architecture
Provide subject matter expertise in the Reinsurance domain for data analytics.
Architect and oversee the integration of Power BI with various data sources, including Azure Data Lake Storage, Databricks, and other cloud or on-premise data platforms.
Define analytic solution leveraging Databricks, DBT and Power BI.
Develop and enforce development standards, governance policies, and best practices to ensure consistency, security, and maintainability across all reports and dashboards.
Support the deployment of Power BI in enterprise environments, including managing data refresh schedules, security roles, and workspace governance.
Identify and address performance bottlenecks in data pipelines and queries.
Implement strategies to optimize data processing and reduce latency in data delivery
Optimize Power BI performance by implementing best practices in data modeling, query optimization, and report design.
Produce comprehensive design documentation, deployment plans, and user guides.
Stay current with Power BI innovations and industry best practices, recommending improvements to enhance reporting capabilities.