Top Analysis Reporting Jobs in Madison, WI

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

Design, build, and operate large-scale AWS-based ETL pipelines using Glue/PySpark to ingest, transform, and curate multi-format data into Apache Iceberg tables. Ensure data quality, metadata management, semantic layer creation (Trino/Athena), CloudFormation deployments, documentation, and compliance within a FedRAMP federal agile environment.

Perform customer analytics and lifecycle measurement for subscription and auto insurance products. Build dbt/Snowflake data models, Tableau dashboards, survival and churn analyses, propensity datasets, A/B tests, pricing and LTV analyses, and recommendation logic. Partner with data engineers, data scientists, product, and marketing to operationalize personalization and inform retention, pricing, and product strategies.

The role involves leading comprehensive testing of Federal Amazon Connect solutions, ensuring compliance with security standards, mitigating risks, and collaborating with cross-functional teams to deliver high-quality products.

Review TEFCA participant and subparticipant directory entries against authoritative sources, apply a documented review methodology, classify dispositions, document findings and evidence in Jira, escalate exceptions, participate in QA sampling, and maintain throughput and audit-ready case notes for federal health IT compliance.

Design and build end-to-end geospatial data systems: ingest and process satellite imagery into columnar/chunked stores, expose results via GraphQL/REST and FastAPI, build Next.js/React dashboards, automate with IaC and CI/CD, orchestrate pipelines with Prefect, optimize petabyte-scale I/O, and lead hiring, mentoring, and engineering best practices.

Define and lead the technical architecture for a lakehouse on AWS, build production pipelines and data models for time-series and multi-source data, introduce data governance and catalog foundations, author platform playbooks (ADRs, runbooks, Terraform modules), deliver projects end-to-end, and mentor engineers while representing the platform to senior leadership and non-technical stakeholders.

Design, build, and maintain scalable ETL pipelines and data warehouse architecture using BigQuery, Databricks, and GCP. Ingest and transform high-volume data from Postgres, REST APIs, and other sources, improve reporting, create reusable code and tests, and collaborate in an Agile/SCRUM environment.

As a Credit Risk Senior Analyst at Marqeta, you'll lead underwriting strategies, refine credit policies, conduct risk analyses, and present findings to senior management.

Build and maintain Sigma dashboards, analyze client workup data, develop predictive models to forecast case progression, evaluate team productivity, translate data into actionable insights, document methodologies, and collaborate with data engineering and legal teams to improve reporting and operations.