Top Analysis Reporting Jobs in Baton Rouge, LA

The Data Integration Engineer will manage data integrations and ETL processes for healthcare data, ensuring accuracy and accessibility for business users.

This role involves valuation, pricing and product development, modeling, forecasting, and risk management tasks related to life insurance and annuity products.

The Data Strategist will manage M&A integration by creating financial models, prioritizing data requests, and collaborating cross-functionally to optimize data value and operational efficiency.

As the Client Insights Lead Analyst, you will create analytics strategies, lead data analysis, collaborate with teams, and communicate insights to clients effectively.

Own and improve the dbt modeling and semantic layers, implement CI/CD, tests, observability, and governance; build governed metrics for BI and AI consumption; partner with Data Engineering and Risk to stabilize pipelines and improve data quality and documentation.

Lead enterprise data strategy and governance engagements; advise C-suite clients; design governance frameworks (MDM, metadata, data quality, access controls); oversee delivery, mentor leaders, drive business development and thought leadership; align modern data stack to business outcomes.

The Product Analyst will analyze product performance, manage workloads, document processes, support product reviews, and generate reports while collaborating with teams.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Senior individual contributor in People Analytics leading workforce analysis, dashboards, data quality, and insight generation to inform HR and business decisions. Partners with talent, engagement, and planning teams to produce scalable analytics, benchmarks, and recommendations.

Own and build reliable analytics data products: define metrics, create and maintain dbt models, design dashboards for growth/finance/ops, improve data quality via testing and monitoring, and enable self-serve analytics for stakeholders.

Design, build, and maintain scalable data pipelines and models; collaborate with analysts and data scientists to provision prepared datasets; implement data quality, governance and monitoring; recommend technologies; lead root-cause analysis, code reviews and testing; mentor teammates and support production data environments.