Top Analysis Reporting Jobs in Indianapolis, IN

The North America Segment Analyst supports marketing activities related to forecasting, market analysis, and product development, collaborating closely with sales and marketing teams.

The Performance Analyst analyzes technology performance data to inform decisions, develop dashboards, and improve reporting processes. This role involves evaluating data trends, supporting KPI strategy execution, and collaborating with teams for process improvements.

Design, develop, test and implement ETL processes for a new Collection platform. Build SSIS packages on SQL Server 2008, write Unix shell scripts, integrate with .NET/C#/VB.NET or other ETL tools (Informatica, DataFlux, Pervasive), and communicate with stakeholders to deliver reliable data pipelines.

The Analytics Engineer will design data models, maintain analytics pipelines, document data governance, and partner with stakeholders to address data needs.

Build and own customer data ingestion and large-scale pipelines powering AI workers. Design syncing, retrieval, and data lake systems, improve reliability/observability, partner with product/backend teams, and contribute across infrastructure to give AI agents access to enriched customer data.

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

The Quantitative Researcher will analyze crypto markets, build trading strategies, and develop systems for performance analysis and risk management.

The Director of Data Intelligence role involves leading a team to drive client success through data, AI, and visualization, fostering a culture of continuous improvement, ensuring delivery excellence, and participating in business development and innovation initiatives.

The role involves driving the identification of requirements, improving systems processes, developing prototypes, and ensuring usability in product development projects within an AI company.

Design, build, and maintain scalable cloud data pipelines and Databricks-based data platforms. Manage Databricks clusters and Delta Lake tables, integrate with Azure services, implement CI/CD and monitoring, define data warehouse architecture and governance, collaborate with stakeholders, and support advanced analytics and future AI/ML use cases.