Top Analysis Reporting Jobs in Tampa, FL

Design and develop data pipelines, integrations, transformations, and infrastructure across AWS, Snowflake, Airflow, and MySQL. Troubleshoot warehouse issues, validate data quality, improve pipeline reliability, and translate business needs into data engineering solutions. Interpret technical findings for client recommendations, manage workstreams, review junior team members’ work, and provide technical guidance across managed services engagements.

Owns go-to-market funnel reporting and analytics from lead generation through pipeline, bookings, and ARR. The role analyzes conversion, pipeline quality, CAC, LTV, marketing ROI, and sales efficiency across segments and channels. It builds dashboards, forecasts, and executive insights while partnering with Marketing, Sales, Revenue Operations, and Finance on attribution, data integrity, budgeting, and investment decisions.

Leads enterprise sanctions-screening analytics strategy, developing KPI frameworks, governance standards, dashboards, root-cause analyses, and predictive insights. Identifies false-positive drivers, workflow bottlenecks, and automation opportunities while recommending tuning and process improvements. Partners with technology, operations, compliance, and governance stakeholders to build business cases, implement analytics-enabled automation, monitor performance, and deliver executive-ready reporting.

Leads customer insights management for Insurance Operations, translating customer, experience, and operational data into executive recommendations. Oversees KPIs, reporting, research, journey mapping, customer analytics, root-cause analysis, AI-enabled insights, and cross-functional improvement initiatives. Shapes the customer experience strategy and roadmap, manages team priorities and resources, leads strategic projects, and develops team capabilities through coaching and cross-training.

Leads business intelligence and analytics for Verizon’s Business Markets Group. Designs measurement programs, develops advanced geospatial and financial models, evaluates sales and operational approaches, standardizes metrics, and converts complex data into strategic insights. Partners with business, technology, marketing sciences, and operational analytics teams while leading cross-functional data initiatives.

Lead data analysis supporting USCENTCOM’s data lake, machine learning initiatives, and intelligence operations. Responsibilities include researching and testing data methodologies, analyzing large datasets, developing data pipelines, integrating analytics tools, establishing metrics, visualizing findings, and advising military clients and stakeholders. The role requires translating complex data into actionable recommendations and supporting intelligence products through quantitative and qualitative analysis.

Designs, develops, and supports enterprise analytics solutions using Power BI, Microsoft Fabric, SQL, semantic models, dashboards, reports, dataflows, and automation. Partners with operational, clinical, financial, and technology stakeholders to translate business needs into trusted insights. Advances governed self-service analytics, data quality, security, documentation, AI-enabled analytics, visualization, and reporting automation while supporting continuous improvement and an on-call rotation.

Build, deploy, and support scalable data pipelines and curated data products on Azure Databricks. Integrate enterprise data sources using batch and streaming patterns, transform data with SQL and Python/PySpark, and implement Delta Lake, dimensional modeling, governance, monitoring, testing, and CI/CD. Collaborate with technical and business stakeholders to deliver reliable, documented data products for analytics, reporting, and AI use cases while improving platform performance, security, quality, and cost efficiency.

Leads the design, development, testing, tuning, and optimization of financial crimes detection models across AML, fraud, KYC, and sanctions. Performs statistical analysis, threshold calibration, back-testing, model efficacy assessments, feature engineering, and root cause analysis. Configures financial crimes platforms, monitors model performance, establishes testing and governance standards, and partners with Model Risk Management and leadership on validation, audit, regulatory, and risk-related initiatives.

Designs, builds, and operates large-scale Hadoop-based data pipelines and analytics platforms. Responsibilities include ingesting, transforming, streaming, and analyzing structured and unstructured data; developing Spark applications; managing distributed systems; supporting machine learning and reporting workloads; troubleshooting production environments; and improving platform reliability, performance, and cost efficiency.