Top Senior Analysis Reporting Jobs in Indianapolis, IN

Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.

Lead design and delivery of Snowflake-centric cloud data platforms. Engage with clients to gather requirements, architect scalable secure solutions, provide technical leadership, develop roadmaps, advise executives, and guide implementation best practices across the analytics stack.

Perform hands-on Epic data conversion activities including CCDA/PAMI ingestion, source-to-target mapping, ETL, data validation, reconciliation, mock conversions, cutover support, troubleshooting, and documentation to ensure accurate migration of clinical and operational data from multiple legacy EMRs into Epic.

Lead revenue analytics for GTM: own annual operating plan and weekly forecast, build propensity/churn/expansion models, architect the revenue data warehouse and identity resolution, define TAM/ICP, leverage AI to automate insights, and partner cross-functionally to maintain single-source-of-truth revenue metrics.

Own and operate the Snowflake warehouse and Sigma semantic layer; manage ingestion (Fivetran), dbt model scoping and review, reverse-ETL, data quality SLAs, dashboards, month-end financial analytics, vendor management, and automation to support AdOps, Sales, Finance, and executive reporting.

Own and scale Provable's data platform on GCP: build and optimize ingestion pipelines from blockchain indexers, design privacy-aware data models, manage Postgres and BigQuery, develop high-performance data-serving APIs, ensure data quality and observability, and use IaC (Terraform, Helm) and Kubernetes to deploy and cost-optimize environments.

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.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Develop and maintain ETL solutions, optimize processes, validate data, and support production issues. Collaborate with analysts for efficient data integration.

Analyze portfolio-level organic search performance to identify trends and opportunities, build dashboards and benchmarks, define KPIs, evaluate strategy and product impacts, partner with Product/Data/Engineering, and translate insights into clear recommendations for technical and non-technical stakeholders.