Top Data & Analytics Jobs in Indianapolis, IN

Lead business intelligence strategy across product, clinical, commercial, finance, and engineering teams. Build measurement frameworks, semantic layers, reporting solutions, and visualizations that demonstrate business value and support data-informed decisions. Own the data lifecycle from ideation through client-facing delivery, ensure data governance and integrity, and translate complex datasets into actionable insights. Collaborate on scalable data architecture and apply statistical methods, advanced analytics, and emerging AI-driven BI capabilities.

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.

Bachelor-level intern supporting behavioral health operations through client interaction, public speaking, team meeting facilitation, and data work. The intern will receive training in Microsoft Excel, data cleaning and analysis, data visualization, and storytelling through one-page reports and presentations. The role requires strong written and verbal communication, attention to detail, independent work, and the ability to manage multiple priorities.

Designs and manages advanced analytics models and reporting tools for supply chain, inventory, fulfillment center labor, and operational performance. Builds predictive analytics to forecast key metrics, automates reporting, provides data-driven decision support, collaborates with cross-functional teams, and mentors entry-level analysts.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Design and maintain scalable AWS-based data pipelines, architectures, ETL/ELT workflows, databases, and big data solutions. Integrate and transform complex datasets using Python, SQL, Spark, Hadoop, and Kafka. Build data models, dashboards, reports, and analytics solutions while implementing data quality, governance, security, monitoring, and compliance processes. Support migrations and modernization projects, collaborating with data scientists, analysts, and business stakeholders to deliver reliable, decision-ready data.

Designs and builds scalable data platforms and pipelines for scientific, clinical, manufacturing, and process-engineering data. Responsibilities include developing batch and streaming ETL/ELT systems, integrating Databricks, Snowflake, cloud platforms, MES, SCADA, and laboratory systems, and enforcing governance and GxP compliance. The role provides hands-on technical leadership, establishes data engineering standards, and collaborates with scientists, process engineers, and platform teams. It requires three days onsite weekly in Indianapolis and unrestricted U.S. work authorization.

Build and operate reliable data pipelines transforming flight test, simulation, and operational data into versioned, traceable ML training datasets. Responsibilities include ingestion, normalization, time alignment, validation, dataset lineage, anomaly mining, labeling workflows, deployment feedback loops, monitoring, and data coverage analysis. Collaborate with flight test and operations teams on instrumentation and data access. The role is on-site in Boston and requires production data engineering experience supporting machine learning pipelines.

Supports data preparation, organization, validation, quality control, analysis, reporting, and data governance activities. Assists with data lake development, process documentation, workflow maintenance, and stakeholder collaboration. Participates in projects and meetings to learn how technology and data support business decisions while maintaining confidentiality and following firm policies.

Support digital tools, technology initiatives, project workflows, data management, visualization, and technology-enabled solutions. Collaborate with technical professionals to improve engineering and design team workflows, apply classroom knowledge to real-world challenges, and participate in professional development and networking activities.