Top Analysis Reporting Jobs in Indianapolis, IN

Build and maintain observability across enterprise data pipelines, including data quality checks, freshness, volume, schema monitoring, alerting, incident triage, root cause analysis, SLA management, and runbooks. Configure tools such as Monte Carlo, Great Expectations, CloudWatch, and Datadog to improve pipeline reliability and data trust.

Paid 10-week data analytics internship supporting the Mortgage Purchase Program. Responsibilities include building Power BI dashboards, cleaning and analyzing SQL and enterprise data, validating reports, documenting processes, supporting data governance, gathering requirements, and presenting insights. Interns collaborate across teams and gain experience in finance and banking while developing SQL, Power BI, communication, and problem-solving skills.

Build and maintain scalable Snowflake data pipelines and dbt-based ELT workflows using SQL and Python. Integrate multiple source systems, implement Medallion Architecture patterns, monitor pipeline reliability, resolve data quality issues, and support performance and cost optimization. Collaborate with analytics, product, and business teams to deliver trusted datasets while contributing to data modeling, governance, testing, documentation, lineage, code reviews, and deployment practices.

Develops and maintains Power BI dashboards, cleans and standardizes reporting, creates data dictionaries, organizes datasets, and produces documentation and training resources. The intern supports data preparation for AI/ML initiatives and helps teams improve data accessibility and interpretation. The role requires Power BI or similar visualization experience, familiarity with databases and Excel, strong documentation skills, and at least one year of data or reporting experience through internships, co-ops, or university research.

Analyzes Recidiviz interventions using Python and SQL, builds statistical models, measures historical and projected impact, develops automated metrics workflows, and communicates findings to stakeholders. The role defines product usage and impact measures, supports experimental and quasi-experimental analyses, and informs product strategy and fundraising partnerships focused on criminal justice outcomes.

Build, maintain, and optimize data warehouses and ETL/ELT pipelines supporting ticketing, sales, marketing, fan engagement, and analytics. Integrate NFL and third-party data into Snowflake and Azure, develop modeled datasets, monitor data quality and ingestion, troubleshoot pipeline issues, and document schemas and workflows. The role also supports privacy, consent, data governance, and cybersecurity controls while collaborating with technical and business stakeholders. This is a full-time, onsite position in Indianapolis.

Leads PBM data integration delivery across claims, eligibility, accumulator, and encounter systems. Profiles and validates data, writes advanced SQL, resolves reconciliation discrepancies, investigates production issues, and partners with engineering on scalable healthcare integration architecture. Owns timelines, risks, vendor dependencies, testing, UAT, migration, rollback planning, executive reporting, and post-deployment support. Requires deep PBM claims-processing expertise, data architecture experience, and hands-on knowledge of ETL, secure file transfer, job scheduling, and healthcare data standards.

Designs, develops, tests, troubleshoots, and deploys cloud-based data and analytics solutions using AWS, infrastructure as code, and software development practices. The role involves data integration, automation, application and data model design, system integration, code reviews, testing, troubleshooting, and stakeholder collaboration. It also provides informal leadership through mentoring, design sessions, coding sessions, and communication of complex technical concepts.

Designs, builds, and maintains scalable AWS and on-premises data pipelines supporting genomic data science models. Responsibilities include API ingestion, storage, transformation, data modeling, workflow development, troubleshooting, documentation, infrastructure-as-code, and cross-functional collaboration. The role requires hands-on AWS pipeline development, HPC experience, container orchestration, Python and SQL expertise, CI/CD, secure access management, and production data engineering leadership in a consulting environment.

Performs structured data analysis under senior guidance to solve customer problems, identify patterns and anomalies, test hypotheses, and develop reusable data science components. Collaborates with engineering, mission operations, solution delivery, and customers to scope requirements, improve processes, and translate analytical findings into actionable business decisions. The role requires strong communication, coachability, analytical coding ability, and willingness to travel up to 50%.