Top Senior Data & Analytics Jobs in Orlando, FL

Leads client-facing data engineering engagements by designing scalable data architectures, pipelines, models, and schemas. Translates business requirements into technical solutions, optimizes data delivery and automation, and supports analytics initiatives. Mentors data engineering teams, collaborates with technical and business stakeholders, contributes to proposals and estimates, and manages project communications. The role requires consulting expertise, strong SQL and big data skills, cloud experience, and frequent client travel.

Leads Alteryx’s product telemetry and analytics function, including instrumentation, semantic-layer governance, self-service analytics, intake prioritization, capacity planning, and executive communication. Manages a team in India, develops talent, improves data adoption and trust, and partners with technical and business leaders to sequence platform work. The role requires expertise in product analytics, data architecture, analytics operating models, metric governance, and stakeholder enablement.

Leads and develops the data analytics team while owning the analytics strategy, roadmap, and self-service reporting capabilities. Designs Power BI dashboards, SSAS Tabular models, and SQL-based analytics solutions across enterprise data platforms. Partners with executives and stakeholders to translate data into actionable insights, improve governance, and promote data-driven decisions. Drives AI-augmented analytics initiatives involving Microsoft Fabric, Copilot, Azure OpenAI, predictive reporting, natural-language querying, and responsible AI practices.

Lead growth analytics for Zendesk’s product-led growth motion, guiding a team of analysts and partnering with Product, Engineering, Sales, Marketing, and Data teams. Define funnel metrics, measurement plans, experiments, and instrumentation across acquisition, activation, conversion, retention, and expansion. Analyze customer behavior using segmentation, cohorts, funnels, experimentation, and statistical methods. Improve self-service reporting, dashboards, metric definitions, reusable datasets, and analytics capabilities while coaching analysts and influencing senior stakeholders.

Oversee client data pipelines, automated ETL/ELT workflows, data quality, and governance while leading advanced marketing measurement applications such as Media Mix Modeling, causal impact, and market testing. Direct data management efforts within GCP, guide product and technical roadmaps, collaborate with media analytics teams, and present technical insights to client stakeholders.

Owns marketing performance reporting, KPI frameworks, attribution, funnel measurement, and dashboard development across digital channels. Builds and integrates web, CRM, sales, and customer datasets using SQL, Databricks, BigQuery, and visualization tools. Analyzes user behavior, campaign performance, conversion, retention, and revenue influence to recommend personalization and optimization strategies. Partners cross-functionally with Marketing, Sales, IT, Finance, and Data teams while ensuring data quality, privacy compliance, and consistent tracking taxonomies.

Design, develop, and maintain enterprise data solutions and pipelines using Azure data platform and Microsoft Fabric. Support data modeling, master data management, medallion architecture, data quality, and integrations to produce trusted, scalable data for analytics and BI.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

Build and maintain scalable data processing pipelines and the data warehouse, write tested performant code, develop product features, establish data engineering standards, and collaborate across product and engineering to improve data access and quality.

Analyze in-park revenue and guest behavior to optimize pricing, promotions, and product mix across Food & Beverage, Retail, Ancillary, and Zoo operations. Build and maintain dashboards, conduct ad hoc analyses and financial modeling, support vendor analytics tools, partner with Finance/Marketing/Operations, and uphold data governance to drive revenue growth.