Top Senior Analysis Reporting Jobs in Indianapolis, IN

The Data Analyst will support operational reporting and stakeholder needs, working with SQL and Artiva to meet business requirements through data and reporting solutions.

As a Senior Analytics Engineer, you will own Solv's analytics stack, focusing on data pipeline efficiency, customer-facing analytics, and AI-powered tools, working with internal teams to improve metrics, dashboards, and data visibility.

As Senior Manager of IT Commercial Data Management, you will lead data initiatives, manage product ownership, and develop data governance strategies in collaboration with stakeholders, ensuring high data quality and analytics capabilities.

The Staff Data Engineer will architect and implement a next-generation data platform, build data pipelines, and ensure data integrity for actionable insights.

The Senior Engineer, Data will architect and deploy data pipelines, optimize databases, collaborate with teams, and maintain data integrity. They will also enhance data architecture and improve processes using various technologies.

The Solutions Consultant will conduct product demos, assist in sales cycles, and provide evidence of product value while maintaining product knowledge and client relations.

The Senior Data Analyst will conduct quantitative analysis, optimize products through data insights, and lead A/B testing in collaboration with various stakeholders.

The Director of Data will lead the data organization, drive data strategy, oversee the data platform, and ensure high-quality data products across OneImaging, contributing to decision-making in operations and product development.

As a Data Analyst, Growth at Kraken, you will analyze complex marketing data to provide actionable insights that enhance client acquisition, retention, and decision-making through data engineering, reporting, and experimentation.

As a Senior Data Engineer, you'll design and build data pipelines, automate processes, and collaborate with business teams to support analytical needs, ensuring data quality and optimization for ML workloads.