Top Senior Analytics Jobs in Tampa, FL

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Build and scale the analytics foundation: own dbt projects and Snowflake warehouse, create trusted datasets and semantic layers for AI, build ELT pipelines from APIs, implement testing/observability and CI/CD, design reconciliation models, enable stakeholder self-service, and partner cross-functionally to drive data-driven decisions across GTM, Product, Finance, People, and Operations.

Develops and maintains insurance pricing and predictive models, analyzes premiums, losses, claims, and exposure data, evaluates profitability and emerging risks, supports rate filings and actuarial analyses, and delivers recommendations to leadership. The role also ensures data integrity, prepares financial reporting, automates workflows, and collaborates with product, actuarial, and business teams to improve pricing strategies and operational efficiency.

Lead strategic revenue cycle analyses to diagnose patient billing and collections performance, quantify ROI and value, build executive-ready recommendations and playbooks, partner cross-functionally, and mentor teammates to drive scalable, data-driven improvements.

Lead architecture, systems, and roadmap for Coinbase's Compliance Reporting Data Platform. Design and build production-grade data models, pipelines, quality frameworks, validations, and certification processes. Establish data contracts, monitoring, reconciliation, and audit-ready processes. Partner with engineering and compliance stakeholders, respond to regulatory exams, and mentor engineers while shaping standards and documentation.

Serve as a strategic analytics advisor designing and implementing Adobe Analytics and CJA solutions, conducting measurement workshops and audits, building dashboards, translating insights into action, training clients, and ensuring data security and privacy compliance.

Lead and grow the Revenue Analytics team to deliver strategic sales and customer lifecycle insights. Build forecasting, pipeline, capacity, predictive models, and customer lifecycle analytics to improve revenue, retention, adoption, and expansion. Partner with GTM, Finance, Product, and Enterprise Data to create executive reporting, data governance, AI-enabled self-serve datasets, and integrated analytics that drive business outcomes and support a shift to consumption-based models.

Lead development of scalable, well-tested data products for Revenue: design dbt models, metrics, dashboards, governance, and AI-enable analytics. Drive technical direction, automation, quality, and mentor cross-functional partners to deliver trusted reporting and self-service analytics.

Serve as liaison between Risk Management and IT to design data architecture, perform data modeling, QA/UAT, translate business needs into technical requirements, and deliver analytics and process automation recommendations to improve risk information systems.

Lead design and development of Power BI dashboards and automated HR/Finance reports, build data models, and ensure data governance and accuracy. Define KPIs and performance measurement frameworks, partner with HRIS and HR teams, and provide analytics consulting to HR stakeholders. Use SQL, Databricks, and AWS for scalable reporting, applying descriptive to prescriptive analytics for workforce planning, talent acquisition, performance, and attrition insights.

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Owner of the analytics foundation: design and maintain BigQuery/dbt models, pipelines, and Looker Studio reporting; build AI workflows and web apps on GCP; integrate marketing, e-commerce, and fulfillment data; ensure GCP ops, security, and reliability; use AI-assisted tools daily and collaborate with business and client stakeholders.

Lead a team delivering marketing analytics and consulting: assess offline and digital marketing impact, perform MMM, attribution, pricing/promotion and demand-forecasting, provide analyses, recommendations and client-facing presentations.

Lead and grow the customer analytics practice in Communications, Media & Technology. Define strategies and thought leadership, communicate the value of data and analytics, and lead delivery of large, complex client engagements. Leverage management consulting experience and expertise in customer analytics, CRM modeling, reporting, and predictive analytics tools.

The Principal Analyst leads employee and patient experience surveys, performs advanced analytics, supports job analysis, and strategic workforce planning, providing actionable insights to enhance HR practices.

Technical owner of enterprise Power BI semantic models and KPI frameworks. Design dimensional models, develop advanced DAX measures, optimize model performance, govern metrics, build governed datasets and reports, and support deployments and migrations to Microsoft Fabric/Databricks while partnering with finance, commercial, and operations stakeholders.

Own Chamber’s central analytics and reporting function for value-based cardiology contracts and clinical programs. Build SQL models, governed metric definitions, a semantic layer, data-quality standards, executive and board reporting, payer deliverables, SLA tracking, and clinical analytics foundations. Establish reporting governance so finance, clinical, and operations teams can self-serve trusted insights. This hands-on player-coach role requires healthcare claims and clinical data expertise, value-based care fluency, and the ability to build a reporting function from scratch.

Lead business analytics strategy by developing dashboards, scorecards, KPIs, automated reporting, and performance measurement frameworks. Analyze sales and operational data to identify trends, risks, and opportunities, translating findings into actionable recommendations. Partner with Sales, Operations, Finance, IT, and leadership on forecasting, business cases, analytics modernization, governance, and process improvement. Communicate insights through reporting and data storytelling while mentoring analysts and leading cross-functional initiatives.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Lead product analytics: build and maintain dbt models and Looker dashboards, define KPIs, analyze funnel and user journeys, design and evaluate A/B tests, size roadmap impact, and deliver partner and ad-hoc insights to inform product and executive decisions.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

Lead the design and implementation of scalable data models, transformation pipelines, semantic layers, and analytics engineering solutions. Drive dbt best practices, testing, CI/CD, data governance, quality improvements, performance optimization, and technical standards. Collaborate with analysts, engineers, stakeholders, and clients to translate business requirements into reliable data architectures. Mentor peers, lead technical implementations and delivery workstreams, reduce technical debt, and contribute to shared tooling and frameworks.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.