Top Data & Analytics Jobs in Tampa Bay, FL

Analyze auction data to identify performance drivers and risks, collaborate with commercial teams, and provide actionable insights to optimize DSP outcomes.

As a Data Operations Analyst, you will maintain and enhance Charge Integrity SaaS by utilizing SQL and data analysis to solve complex revenue cycle problems and ensure accurate charge capture.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

The Lead Data Analyst will define KPIs, analyze data trends, build dashboards, and support new product launches, requiring strong SQL and Python skills.

Design and implement scalable go-to-market intelligence workflows and automation. Define business requirements for reports and dashboards, partner with Product and Analytics, improve Data Cloud tool adoption, document processes, support integrations, and deliver automation-aligned pre-sales and client-facing materials.

The Senior Data Engineer will build and maintain data pipelines, optimize data processing, and ensure data privacy and quality within the healthcare tech space.

The Senior Ad Ops Engineer develops and manages data products for marketing activation, focusing on data pipelines, quality validation, and integration with marketing platforms.

The Solutions Architect leads client integration of Cedar's platform, ensuring successful project delivery through client communication and technical expertise while managing complex data structures and operational workflows.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.