Top Business Intelligence Jobs in Indianapolis, IN

Own and optimize the enterprise workforce management platform, including forecasting, scheduling, staffing, intraday performance, shift and PTO bidding, and schedule adherence. Analyze workforce and operational data, identify root causes, create trend and productivity reports, model ROI, and recommend staffing improvements. Partner with analytics and operations leaders, mentor real-time analysts and schedulers, and drive efficiency across service and clinical operations.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Serve as the primary technical escalation point for managed services data and analytics clients. Troubleshoot and enhance Power BI, Fabric, Azure, and other analytics environments; gather requirements; translate business needs into scalable solutions; support client onboarding; maintain documentation; mentor support staff; and partner with client success and consulting teams. The role also contributes to continuous improvement, training, knowledge sharing, and AI-enabled productivity initiatives.

Design and implement end-to-end AI features, scalable data pipelines, ETL/ELT workflows, Generative AI and agentic systems, ML and BI solutions, and MLOps/LLMOps practices across AWS, Azure, and GCP. Apply RAG, embeddings, vector databases, security governance, evaluation, reliability, and guardrails. Own technical workstreams, mentor junior engineers, and promote software engineering best practices in consulting environments.

Leads marketing metrics, insights, and reporting initiatives across business areas. Provides project and program analytics, PMO governance, data architecture input, campaign performance analysis, A/B testing, SEO/SEM and funnel analytics. Partners with marketing, IT, project teams, and business leaders to develop reporting methodologies, manage complex projects, optimize campaigns, and translate data into actionable recommendations.

Lead end-to-end business analysis for data and technology projects: elicit requirements, create BRDs/functional specs/user stories, map processes, profile source data with SQL, build source-to-target mappings and documentation, support agile delivery and UAT, coordinate stakeholders, and present actionable recommendations to clients.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Lead enterprise data architecture across multiple SaaS products by unifying reporting platforms, data models, and analytics capabilities. Assess current systems, define target-state architecture, establish data governance and quality standards, separate analytical workloads from transactional systems, and develop phased migration roadmaps. Guide database, engineering, and BI teams on cloud platforms, integration, modeling, performance, security, and reliability. Enable trusted cross-product reporting, governed self-service analytics, and data foundations for AI and advanced analytics.

Integrate operational data into enterprise data warehouses; design, optimize, and support SSIS ETL pipelines; develop SSRS and Power BI reporting solutions and reusable data models; deliver data migrations and self-service extracts. Design production AI/ML solutions using Python, OCR, AWS Bedrock, and Claude, including multi-agent LLM implementations. Partner with stakeholders, lead code reviews, mentor developers, and support production BI deployments.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

Lead data product strategy and governance for customer-facing reporting within Managed Services. Own reporting product roadmap, data quality, standards, delivery platforms (Redwood Insights, BI, Snowflake, Excel), implementation readiness, and cross-functional alignment to scale trusted, automated customer analytics and reduce manual reporting.

Administer Lilly’s enterprise Microsoft Fabric and Power BI platforms across development, QA, and production. Responsibilities include deployments, upgrades, high availability, disaster recovery, gateway and dataset performance optimization, governance, auditing, capacity planning, automation, monitoring, troubleshooting, and cloud integrations across Azure, AWS, Snowflake, and Databricks. The role also develops PowerShell and REST API automation, supports security and networking integrations, mentors administrators, establishes procedures, and serves as the platform subject matter expert.

Design, build, and support enterprise BI solutions including reports, dashboards, ETL/ELT, data marts, governed datasets and production support. Translate business requirements into technical designs, perform complex data analysis and root-cause investigations, document lineage and runbooks, optimize solutions, enforce data governance, and provide technical leadership or mentorship for large-scale initiatives.

Designs and maintains data warehouses, semantic models, metrics layers, pipelines, dashboards, and certified datasets. Establishes KPI governance, data security, row-level access controls, quality standards, and observability. Builds Sigma, Power BI, and Databricks dashboards, supports self-service analytics, resolves BI issues, and enables AI/ML use cases. Collaborates with architecture, engineering, analysts, and business stakeholders to define requirements, document solutions, train users, and drive BI adoption.

Own and enhance Sigma dashboards and business intelligence reporting for the Records Retrieval business. Partner with stakeholders to translate business needs into scalable data solutions, analyze complex datasets, improve data quality and governance, define reporting standards, and support Snowflake data warehouse and modeling initiatives. Deliver actionable insights, automate reporting processes, evaluate analytics tools, and independently drive analytics projects from requirements through delivery.

The Business Intelligence Architect leads BI solutions, analyzes requirements, implements BI applications, and collaborates with remote teams and vendors.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Develop and deploy business intelligence solutions, dashboards, data structures, and visualizations using Tableau and Power BI. Partner with sales, finance, IT, and business stakeholders to turn complex data into actionable insights, enable self-service analytics, consolidate data, and establish analytics standards. Present findings to senior leadership, support forecasting and planning processes, train business teams, and provide ongoing analytics support.

Lead a BI engineering team, overseeing dashboards, data models, SQL/dbt transformations, ETL pipelines, Airflow DAGs, data warehouses, CI/CD, governance, and quality standards. Partner with stakeholders to define reporting requirements, conduct advanced analyses, manage Agile projects, and develop data strategy. Mentor team members and support production deployments. This fully remote role requires travel to Denver for five business days each quarter.

The BI Engineer administers enterprise BI and analytics platforms, governs data consumption, and develops dashboards, reports, KPIs, and self-service analytics. The role translates business requirements into scalable, validated solutions; manages access controls, metadata, data quality, continuity planning, platform costs, and process improvements. It also provides stakeholder consultation, resolves complex technical issues, mentors teammates, and supports enterprise data transformation using Power BI, Tableau, Azure, SQL, and multiple database technologies.

Designs enterprise Power BI semantic models and executive dashboards, translating ambiguous business questions into KPIs and visual narratives. Integrates data from enterprise sources, improves data quality with engineering teams, and establishes governance for accurate, auditable reporting. Mentors BI professionals, defines modeling and metric standards, optimizes performance and scalability, and influences senior stakeholders through trusted insights.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.