Top Analysis Reporting Jobs in Indianapolis, IN

Analyzes customer loyalty data to generate actionable insights, recommendations, visualizations, and narratives for clients. Builds audience lists, applies segmentation and statistical modeling techniques, develops test plans, and collaborates with CRM, Data Engineering, Business Intelligence, Strategy, and Client Services teams. The role is client-facing and manages request prioritization while supporting loyalty marketing initiatives and measurable business outcomes.

Lead migration of financial data pipelines from Snowflake to AWS, design SOX-compliant dimensional models, build Medallion Architecture datasets, implement data quality, observability, CI/CD, and performance optimizations, and partner with stakeholders to deliver production-ready financial analytics at scale.

Supports R&D, packaging, processing, commercialization, and design reporting. Gathers and analyzes data to identify trends, develops dashboards and reporting solutions, trains end users, and provides business insights and process recommendations. Serves as a liaison between IT and the R&D team while improving reporting and decision-making effectiveness.

Leads Allegion’s Data & Analytics team, overseeing data warehouse and lakehouse architecture, Power BI semantic models, self-service BI, and data management services. Manages Analytics and Data Engineers while providing hands-on technical direction. Responsibilities include roadmap development, master data management, data lifecycle and archival solutions, stakeholder collaboration, code governance, process improvement, and team development.

Build and operate a large-scale enterprise data platform spanning batch and streaming processing, lakehouse storage, Kafka infrastructure, APIs, observability, and agentic MCP interfaces. Develop reusable ingestion and data-quality frameworks, improve scalability and resilience, establish engineering practices, support production operations, and mentor engineers. The role requires deep ownership of distributed data infrastructure and practical use of AI coding agents.

Build and transform commercial data solutions using SQL and Databricks, create executive dashboards in Tableau and Power BI, and translate ambiguous business questions into actionable insights. Partner with commercial stakeholders on sales, retail-out, and distribution analytics; identify business trends, standardize reporting, and support enterprise self-service analytics and data maturity initiatives.

Analyze Medicare and Medicaid datasets, design analytical approaches, review R and SAS programming, build healthcare financial models, and translate complex findings into visualizations, presentations, publications, and policy recommendations. The role manages multiple consulting projects, collaborates across teams, presents results to clients, and supports healthcare policy and business decisions.

Supports electronics hardware process improvement through data analysis, engineering tool development, process compliance, dashboards, KPIs, and reporting. The intern analyzes engineering processes and project data, develops visualizations, assists with tool configuration and testing, documents processes, creates training materials, and collaborates with engineering, process, and IT teams to improve efficiency and reporting.

Supports client data integration by analyzing file structures, creating source-to-target mappings, configuring imports, validating transformations, troubleshooting ingestion failures, and supporting onboarding. The role performs testing, production support, documentation, and process improvement while collaborating with clients, QA, implementation managers, and ETL developers. It requires data mapping, ETL familiarity, SQL knowledge, and experience handling CSV, XML, and JSON files.

Owns the analytics layer between curated enterprise data and business users. Builds governed Gold-layer data products, dimensional models, Power BI semantic models, standardized metrics, and reusable data assets. Implements Unity Catalog governance, metadata, lineage, security, quality monitoring, reconciliation, and deployment controls. Partners with analysts, business owners, IT, data stewards, and AI engineers to deliver trusted, documented data for self-service analytics and AI consumption.