Top Data & Analytics Jobs in Indianapolis, IN

Lead development and delivery of operational Receivables reports, dashboards, and analytics. Improve KPI visibility, data integrity, and automation across Collections, Cash Applications, Credit, and Accounts Receivable. Build scalable BI solutions, validate multi-system data, standardize reporting governance, partner with Finance and operational stakeholders, and provide actionable insights to drive performance improvements.

Lead development and delivery of Tableau dashboards: gather requirements, blend complex data sources (Oracle, MS SQL), design and prototype visualizations, administer Tableau site, deploy dashboards, mentor team, support Medicaid stakeholders, and define governance and standards.

Lead data quality and reporting for complaints and servicing systems: cleanse and validate data, build reports and dashboards, perform advanced statistical analyses, automate data extraction, maintain databases, and collaborate with stakeholders to surface actionable insights and process improvements.

As a Snowflake Data Engineer, you will design and maintain scalable data pipelines, optimize SQL transformations, and support analytics platforms, collaborating with stakeholders.

Process and QA/QC geospatial sensor data (LiDAR, GPR, GNSS, UAS imagery), convert and standardize datasets for CAD/GIS/BIM, produce 2D/3D deliverables, maintain templates and archives, and collaborate with field and CAD/GIS teams to ensure accurate, client-ready mapping outputs.

Lead end-to-end FOIA data migration projects into RelativityOne, define and prioritize migration tooling, author requirements and runbooks, engage agency customers, ensure FedRAMP-compliant handling of DT1 data, and drive continuous improvement and product feedback.

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.

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.

Responsible for creating and maintaining technical documentation for developers, ensuring clarity and effectiveness in conveying product capabilities and usage. Collaborate with engineering and growth teams to enhance resources while gathering feedback for continuous improvement.

Lead and grow a data engineering team to build a trusted, fast, composable, and self-serve data platform. Define architecture and roadmap for ingestion, transformation, governance, and analytics; ensure reliability, observability, and security; partner cross-functionally with Product, Analytics, Security, and Engineering; be a hands-on player-coach delivering scalable data systems using Snowflake, dbt, and self-serve analytics.