Top Senior Data & Analytics Jobs in Indianapolis, IN

Build and configure a government Databricks workspace, develop ingestion and integration pipelines from enterprise and legacy systems, and prepare data for reporting. Implement Unity Catalog governance, metadata management, auditing, and lineage; configure MLflow workflows; assess security controls for sensitive data; and create architecture documentation, data dictionaries, and SOPs to support long-term sustainment.

Develops healthcare reporting and analytics solutions using Power BI and SQL to improve operational and clinical performance. Responsibilities include gathering requirements, validating data quality, creating dashboards and reports, partnering with data engineering and advanced analytics teams, training users, maintaining documentation, managing reporting timelines, and resolving data or logic issues.

Lead the design and optimization of healthcare data pipelines integrating EHR, payer, HIE, and vendor data. Build AWS-based ETL/ELT infrastructure, reusable integration tooling, data quality monitoring, and ML enablement foundations. Ensure HIPAA-compliant handling of clinical data, including security controls, audit logging, encryption, and de-identification. Provide technical leadership, mentor engineers, influence platform architecture, and lead complex partner integrations involving FHIR, HL7v2, CCDA, and healthcare terminology standards.

Build and maintain commercial data pipelines, transformations, models, integrations, and data products in Snowflake. Responsibilities include data modeling, quality validation, monitoring, troubleshooting, backfills, operational automation, documentation, and stakeholder collaboration. The role supports analytics, reporting, Streamlit, and AI-enabled use cases while maintaining reliable production workloads, privacy controls, and engineering standards.

Owns governance, quality, standards, and lifecycle management for eight master data domains across ERP and related systems. Administers NetSuite master data, defines validation and error-proofing controls, resolves data discrepancies, maintains audit-ready documentation, and reports quality KPIs. Partners with IT, Supply Chain, Finance, Commercial, Regulatory, Customer Care, and other teams on integrations, migrations, product launches, compliance, serialization, and pricing. Provides cross-functional guidance and drives data discipline without direct authority.

Leads competitive intelligence and market analysis for Medicaid, DSNP, and Marketplace RFPs. Reviews competitor responses, identifies gaps and differentiators, develops recommendations, maintains intelligence databases, supports capture strategy and oral presentations, and advises business development, product, legal, and executive stakeholders. Provides benchmarking, proposal analytics, training, and protest support while refining RFP methodologies. Requires 50% or more travel.

Conducts operations research and advanced analytics to optimize public-sector command performance and reduce costs. Develops optimization, statistical, simulation, regression, mathematical, and decision-analysis models; implements analytical models in Python; performs data analysis; supports software development; assesses operational questions; and prepares decision briefings, reports, presentations, and recommendations for senior leadership.

Lead the design and operation of a scalable data platform, owning ingestion, orchestration, observability, lineage, data modeling, contracts, and ETL/ELT pipelines. Build Databricks and PostgreSQL solutions, implement data-quality controls, anomaly detection, governance, privacy, and compliance practices, and establish reusable engineering standards. Mentor engineers and ensure reliable, traceable data across markets and product lines.

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.