Top Remote Analytics Jobs in Indianapolis, IN

Support the DARL team by building dashboards, automating reporting, and improving data processes. Assist with emissions accounting, regulatory reporting, physical climate risk assessment, and LP engagement for firm-wide sustainability analytics.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

Join the BizOps & Analytics team embedded in a core business area to define problems, build analyses and reports, design experiments, surface insights, and drive data-informed decisions end-to-end to increase customer growth and business scale.

Embedded on a core business unit, own end-to-end analytics: define problems, design metrics and experiments, pull and analyze data, build reports, surface insights, and drive recommendations to inform product, growth, AI, or partnership decisions. Influence stakeholders and execute on outcomes.

Embedded on a BizOps & Analytics team, you will define problems, build reports and analyses, design experiments, surface data-driven insights, and drive cross-functional decisions across growth, product, AI, or partnerships to improve key metrics and outcomes.

Embed with a core business area to define problems, build metrics, run analyses and experiments, generate actionable insights, and drive product, growth, AI, or partnership outcomes end-to-end.

Lead end-to-end analytics for an assigned business area (growth, product, AI, or partnerships). Define problems, build metrics, reports, experiments, and analyses, surface insights, and drive recommendations and execution to improve key business outcomes.

Embed with a core business area to define problems, build reports, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI, or partnerships.

Lead a team supporting Epic analytics and clinical/operational systems. Oversee daily operations, project coordination, testing, reporting, data governance, staffing, training, and vendor interactions. Design scalable data models and pipelines (Microsoft Fabric, SQL Server, Power BI), ensure data quality, and present findings to executive stakeholders while maintaining system availability and compliance.

Build and maintain data infrastructure, integrate veterinary partner systems, develop dbt models and pipelines, provide analytics modeling, testing, reporting, and deliver actionable insights to customers and internal teams.

Lead and grow a BI and analytics team to build scalable, AI-enabled reporting and self-service analytics. Partner with cross-functional stakeholders to deliver executive dashboards, standardize metrics, ensure data quality and governance, and use AI tools to automate insights and accelerate dashboard development.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design, build, and own Sardine's internal data platform and billing infrastructure. Implement and maintain ETL/ELT pipelines, warehouse partitioning, access controls, and data governance. Partner with stakeholders to define KPIs, produce dashboards, and ensure data quality for executive, GTM, product, and finance teams.

Implement, audit, and optimize Google Analytics and GTM tracking; ensure data integrity and ingestion into the data warehouse; run analyses, A/B tests, and funnel/segmentation work; document implementations and collaborate with marketing, product, and data teams to provide actionable insights.

The Data and Analytics Consultant will design, develop, and implement data reporting, visualizations, and analytics solutions for clients while assisting them in data understanding and value extraction.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

The Senior BI Analytics Engineer will design and deliver data models for analytics, ensuring data quality, and collaborating across teams to enhance AI-driven reporting and querying capabilities.

The Analytics Engineer will design data models, maintain analytics pipelines, document data governance, and partner with stakeholders to address data needs.

The Analytics Engineer will develop and maintain analytical data models, manage ELT pipelines, document data governance, and partner with stakeholders to meet their data needs.

The Analytics Architect will design and implement cloud-based analytics solutions, maintain data pipelines, ensure data quality, and collaborate with teams to enhance operational efficiency.

Lead operations analytics for fulfillment: build and own KPIs and dashboards, detect inefficiencies, deliver actionable recommendations, and develop forecasts and capacity models to guide operational decisions.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.