Top Remote Analysis Reporting Jobs in Tampa, FL

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Design, build, and operate scalable data transformation pipelines and dimensional models using dbt, SQL, and AWS. Implement infrastructure-as-code (AWS CDK), CI/CD, and query performance optimizations while ensuring data quality, governance, and collaboration with cross-functional and offshore teams.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Lead payments business intelligence and operational analytics: define KPIs, build and maintain dashboards, ensure data integrity and timely refreshes in Databricks/SQL, run financial and profitability analyses, develop pricing tools, support cross-functional operational reporting, and communicate actionable insights to Payments leadership.

Design, build, and optimize scalable cloud data pipelines and infrastructure. Maintain and refactor SQL and ETL processes, automate data workflows, ensure data quality/security, and troubleshoot complex issues. Provide technical leadership and mentor junior engineers while collaborating with stakeholders to translate requirements.

Lead design, development, and optimization of data models, ETL, and reporting within Oracle Fusion Cloud. Investigate and resolve complex IT issues, ensure regulatory compliance, integrate Oracle with cross-functional platforms, document solutions, and support end-users through training and troubleshooting to drive clinical and operational improvements.

Lead technical design and delivery of Databricks lakehouse solutions: gather requirements, design and build scalable pipelines with Spark/PySpark and Python, integrate with cloud, enforce governance, optimize performance, lead code/review/testing/CI-CD, mentor engineers, and liaise with clients.

Lead Master Data operations: maintain and cleanse master data, enforce governance, act as SME across systems, break projects into executable tasks, track progress, support integrations, audits, SOX documentation, and train team members while partnering cross-functionally.

Design, implement, and maintain data quality processes using cloud platforms (Azure/AWS/GCP). Collaborate with stakeholders to define standards, perform data profiling and cleansing, document issues and remediation, generate quality metrics, and support cross-functional teams to improve data architectures and integration.

Design and govern enterprise data architectures within the Informatica ecosystem. Lead data modeling, ETL/integration using Informatica tools, enforce data quality and governance, optimize performance, manage metadata and lineage, collaborate with stakeholders, document solutions, and train teams.

Design, build, and maintain Tableau reporting and dashboards; partner with data owners and technology to integrate Operational and Compliance Risk datasets; analyze trends, create forward-looking reports, ensure reporting controls and audit readiness, manage SDLC and deployments, drive adoption and continuous improvement, and communicate findings to stakeholders.

Analyze customer service performance for satellite teams, drive process and performance improvements, perform gap analysis, present insights to stakeholders, build reports and dashboards, support cross-functional projects, and assist the Customer Service team with issues.

Own and build scalable ELT pipelines and event-driven ingestion in AWS, using Dagster for orchestration. Implement IaC (Terraform), data quality, lineage, monitoring, and troubleshoot cross-system issues while partnering with analytics and product teams to ensure downstream analytical correctness.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.