Top Remote Data & Analytics Jobs in Tampa, FL

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

The VP Global Grid Modeling will lead global data strategy, manage high-performing teams, ensure quality datasets, and engage with customers for insights in energy markets.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.