Top Remote Data & Analytics Jobs in Tampa, FL

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Own the architecture and hands-on development of Tala’s shared data and analytics platforms. Build semantic layers, governed business metrics, data models, pipelines, services, tooling, and AI-enabled analytics workflows. Lead cross-functional technical initiatives spanning Product, Engineering, Analytics, Finance, and Accounting; improve governance, reliability, usability, and documentation; resolve architectural bottlenecks; and mentor engineers through technical leadership.

Performs treasury finance operations, including loan sales, data analysis, reconciliation, and financial controls. Automates recurring workflows using SQL, Python, Excel, and AI tools; maintains and modernizes data pipelines; investigates discrepancies; and communicates insights to technical and business stakeholders. Serves as a subject matter expert on loan data and finance processes while supporting fraud prevention and financial governance.

Own and evolve the analytics platform, including data models, pipelines, metric definitions, semantic layers, dashboards, and self-service data products. Partner with cross-functional stakeholders to translate business needs into reliable technical solutions. Lead data initiatives, improve ELT reliability and governance, resolve quality issues, mentor teammates, and shape the Analytics team’s technical roadmap. The role requires strong SQL, dbt, modern data-stack experience, business communication, and independent execution in an ambiguous environment.

Supports reporting for ultra-high-net-worth clients by onboarding and maintaining portfolio data, generating performance and transaction reports, auditing trades and cash flows, resolving data discrepancies, and managing private equity and alternative investment information in Black Diamond. The role also assists with investment management and billing processes, maintains control procedures, and provides accurate, timely reporting to advisory teams.

Conduct market research and analysis on ADAS, autonomous driving, electronics, and automotive supply chains in North America. Develop forecasts, build industry relationships, identify technology trends, support sales and business development, present insights to stakeholders and clients, and contribute to industry reports and publications.

Collects, consolidates, cleans, analyzes, and visualizes experimental data from analytical equipment, test rigs, and pilot plants. Performs statistical analysis, anomaly detection, experimental design support, equipment validation, and QA/QC activities. Presents findings to technical leadership, identifies process improvements, and helps extract actionable insights from structured and spectral data.

Owns retention analytics for a new Loyalty & Retention organization, including churn definitions, survival analysis, forecasting, experimentation, acquisition attribution, satisfaction analysis, payment recovery, and save-desk performance. The role builds reporting and predictive models from scratch, partners with BI and actuarial teams, influences cross-functional decisions, and presents retention findings and forecasts to executives.

Designs and governs enterprise data architecture supporting VHA EHR modernization, reporting, analytics, clinical systems, and data integration. Responsibilities include data modeling, governance, metadata and lineage management, APIs, ETL, interoperability, data quality, cloud infrastructure, performance optimization, and stakeholder collaboration. The role also leads architectural enhancements through Agile processes and evaluates emerging data technologies.

Build and operate production-grade data pipelines and models connecting marketing, event, operational, and SaaS data into Databricks. Own data quality, testing, monitoring, lineage, orchestration, attribution, identity resolution, and governed semantic-layer contributions. Partner cross-functionally on privacy-aware data flows, event taxonomies, and reliable Growth data products while improving engineering standards and maintainability.