Sr. BIE, Global Risk Management and Claims (GRMC)

About the role

This is an opportunity to get in at the ground floor and help shape the future of data at one of the world's largest insurance organizations. Our team is building a data lake from scratch using AWS technology, onboarding new data vendors and internal sources, and developing AI-driven tools that expand what our stakeholders can do with data.

Responsibilities

• Lead the end-to-end onboarding of new data vendors and internal data sources into the GRMC data lake, spanning scoping and ingestion design through validation, enrichment, and production delivery.

• Design, build, and maintain robust, scalable ETL/ELT pipelines to extract, transform, and load data from a wide variety of sources (internal systems, third-party vendors, APIs) into Redshift and S3-based data lake layers.

• Develop enriched, analytics-ready datasets by combining internal data with external vendor sources, applying data quality checks, and ensuring fidelity from source to consumption layer.

• Build and expand AI-powered reporting solutions (including LLM-assisted insights, automated narrative generation, and intelligent alerting) that extend what stakeholders can do independently with data.

• Design and deliver dashboards and self-service analytics solutions using QuickSight, Tableau, or Power BI that serve Actuaries, Accountants, Legal, Finance, and senior leadership.

• Develop reporting and analytics for the Insurance claims life cycle, identifying new metrics, risk signals, and actionable insights from complex claims data.

• Manipulate and mine data from Redshift, MySQL, and other sources to perform root cause analyses, answer complex business questions, and surface new insights.

• Work with cross-functional stakeholders to define and maintain sources of truth; obsessively monitor data fidelity and own resolution when issues arise.

• Automate manual data processes and complete ad hoc data retrieval and analysis requests that support Actuaries, Finance, Legal, and other partners.

• Partner with engineering teams to ensure data is captured and stored correctly at the source; partner with business stakeholders to translate complex needs into clear data solutions.

• Mentorship & Bar Raising: Provide technical mentorship to junior BIEs, share best practices on pipeline development and data modeling, and participate in hiring loops to help raise the team's technical bar.

Qualifications

• 5+ years of SQL, ETL or Oracle experience

• 4+ years of processing large, multi-dimensional datasets from multiple sources experience

• 4+ years of performing statistical analysis experience

• 4+ years of developing automated reporting experience

• Experience programming to extract, transform and clean large (multi-TB) data sets

• Experience with theory and practice of design of experiments and statistical analysis of results

• Experience with AWS technologies

• Experience in scripting for automation (e.g. Python) and advanced SQL skills

• Experience with theory and practice of information retrieval, data science, machine learning and data mining