Top Senior Analysis Reporting Jobs in Orlando, FL

Owns B2B pipeline and B2C growth analytics, including attribution, acquisition, registration funnels, organic search, forecasting, dashboards, experimentation, and marketing measurement. Partners with marketing, sales, product, data engineering, and leadership to define metrics, improve tracking, deliver actionable insights, and support data-driven decisions. The role also contributes to dbt models, semantic-layer development, analytical quality standards, and mentoring.

Build and guide data platform capabilities supporting marketing, finance, analytics, and data science. Develop data collection, integration, scoring, experimentation, analytics, and infrastructure solutions; contribute code, lead cross-functional technical initiatives, improve system resiliency through incident response, and establish engineering standards. Partner with business and technical stakeholders to define strategy and long-term roadmaps.

Design and operate production-grade data pipelines, backend services, APIs, and agentic AI workflows. Build scalable systems that ingest, transform, and operationalize data for customer-facing and internal applications. Translate ambiguous operational workflows into reliable architectures, improve service observability and performance, and own technical decisions across data modeling, system design, security, and compliance.

Lead GTM analytics across performance measurement, channel economics, data governance, forecasting, planning, and executive reporting. Own metric definitions, data standards, analytical priorities, and business requirements while partnering with Marketing, Data Science, Finance, RevOps, and Engineering. Analyze funnel, attribution, CAC, payback, conversion, retention, pipeline, and territory performance, translating findings into investment recommendations and strategic decisions for senior leadership.

Analyze and document raw healthcare data ingestion into the Bronze layer of a medallion data architecture. Responsibilities include data mapping, lineage documentation, quality monitoring, schema-drift detection, ingestion troubleshooting, and data-health dashboard development. The role collaborates with engineering and analytics teams to improve data accuracy, traceability, and operational excellence across large healthcare datasets.

Performs strategic and business analysis supporting sales, marketing, lifecycle, and product teams. Builds dashboards, recurring reports, business cases, scenario models, and presentation-ready insights. Maintains data quality, identifies performance issues, and supports leadership decision-making. Uses generative AI tools to automate reporting, accelerate analysis, and uncover growth opportunities.

Leads the architecture and hands-on development of an enterprise Microsoft Fabric data platform. Designs Medallion lakehouse layers, ingestion pipelines, Delta Lake tables, dimensional models, data quality controls, monitoring, documentation, and deployment standards. Integrates ERP, financial, HRIS, project, and BI data while optimizing performance and cost. Partners with BI and analytics stakeholders to support governed reporting, forecasting, and future AI-enabled capabilities.

Leads analytics strategy for Zip’s emerging financial products, from market sizing and launch readiness through adoption, retention, risk, and unit economics. Partners with Product, Finance, Risk, and Operations leaders to define metrics, build scalable dbt models and reporting frameworks, analyze customer and portfolio behavior, and guide strategic decisions. Establishes SQL and analytics standards, mentors analysts, and translates complex findings into recommendations for executives.

Contract Analytics Engineer maintaining Looker and LookML dashboards, reporting, data operations, sales pacing, data QA, vendor workflows, board reporting, forecasting, and planning support during a director’s maternity leave. The role requires strong SQL and Snowflake skills, analytics engineering experience, vendor management, Git/GitHub proficiency, documentation, and independent work in a lean data team.

Analyze and model marketing, product, and loan application data to optimize the borrower funnel and drive growth. Build BigQuery datasets, dbt models, and Tableau dashboards; evaluate customer behavior, acquisition costs, approval rates, and origination performance. Partner with Product, Marketing, and Engineering on A/B tests, statistical analysis, and actionable insights for leaders. Apply lending and fintech knowledge to improve conversion, customer value, and portfolio outcomes.