Top Senior Analysis Reporting Jobs in Indianapolis, IN

Own and build scalable analytics models, metric definitions, and dashboards (customer-facing and internal). Partner with engineering to design data flows and instrumentation (BigQuery, S3, PostHog). Translate stakeholder needs into analytics plans, triage requests, and surface insights via Looker/Observable. Set analytics stack direction and ensure data quality.

Lead design, implementation, and optimization of cloud-native data platforms (Snowflake, AWS, Azure) for managed-services clients. Translate business requirements into secure, scalable architectures, drive migrations and performance tuning, and provide hands-on technical leadership. Collaborate with cross-functional teams, mentor junior engineers, and contribute to best-practice frameworks, automation, and pre-sales efforts.

Design, build, and maintain enterprise data warehouses and lakes; implement ETL pipelines; optimize data models and performance; produce analytics and predictive models; create dashboards and visualizations; monitor data quality; document and collaborate with stakeholders to drive data-driven business solutions.

Execute underwriting and case-valuation analytics: write and optimize SQL, build dashboards, maintain valuation models, forecast case outcomes, monitor portfolio performance, and translate insights for operational and marketing stakeholders.

Lead administration and optimization of the Snowflake data warehouse. Design and enforce data management and security policies, tune performance and costs, lead migrations and ETL initiatives, manage Snowflake roles/SSO, mentor DBAs, and maintain architecture documentation while collaborating with data engineers and analysts.

Lead embedded BizOps analytics for a core business area (growth, product, AI, or partnerships). Define problems, build metrics, reports, experiments, and analyses, and drive data-informed recommendations end-to-end to influence leadership and deliver measurable business outcomes.

Own the end-to-end analytics function embedded in a core business area (growth, product, AI, partnerships). Define problems and metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive outcomes with cross-functional teams.

Design, build, and optimize Microsoft Fabric-based lakehouse solutions. Develop scalable ETL/ELT pipelines and Spark notebooks, implement medallion architectures, support CI/CD, governance, lineage, and client-facing collaboration for cloud analytics projects.

Senior Exasol data engineer to design, build, optimize, and validate SQL-based data pipelines for healthcare analytics. Responsibilities include complex query tuning, extracting/staging from SQL Server, chart validation, applying clinical terminologies, quality measure development, and maintaining disciplined version-controlled engineering practices.

Lead design and governance of a large-scale AdTech data layer: model conceptual/logical/physical schemas, profile and map data flows, define batch and real-time ingestion and integration patterns, architect cloud-native AWS solutions (including graph/vector/RAG use cases), establish governance, and produce architecture artifacts and implementation roadmaps while collaborating with engineering, product, and cloud teams.