Top Remote Data & Analytics Jobs in Tampa, FL

Lead strategic analytics and partner with senior leadership to drive growth, margin, and retention initiatives. Build interactive reporting (Python/Streamlit, BigQuery-connected Google Sheets), perform deep EDA in Jupyter, model and clean data with SQL and dbt, integrate secure AI-assisted tools and automation, ensure analytical quality, and translate insights into measurable business outcomes.

Own and maintain the companys data infrastructure and pipelines. Design, build, and monitor ETL/ELT workflows and data architecture; integrate SaaS sources; enforce data quality, standards, and governance; partner with stakeholders to deliver analytics-ready data and meet data availability SLAs.

Design and build large-scale data migration systems, map heterogeneous legacy sources into the platform, ensure end-to-end data correctness, create repeatable tooling, support analytics and BI, optimize performance and storage, debug production data issues, and collaborate with Product, Implementation, and Ops for agency onboarding.

The EHSS & Quality Senior Analyst leads data management for EHS, ESG, and Quality goals, ensuring compliance and driving continuous improvement initiatives. Responsibilities include data collection, analysis, and reporting, as well as the development of dashboards and automation processes.

As a Data Analyst Intern, you will assist in data collection, cleaning, analysis, and visualization to support business decisions in a remote setup.

As a Senior Data Analyst, you will analyze game telemetry data, translate business needs into insights, and guide technical teams. You will also lead exploratory data analysis and maintain data quality practices.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Design, build, and maintain scalable ETL/ELT pipelines and product-level data architectures. Improve pipeline performance and data freshness, lead code/design reviews, mentor engineers, and collaborate with Data Science, Product, and Engineering to make data reliable and accessible.

Support data collection, cleaning, and preliminary analysis. Write and run SQL queries, use statistical tools and Python, produce visualizations, document methods, troubleshoot analytics tools, and collaborate with cross-functional teams to deliver actionable insights.