Top Remote Data & Analytics Jobs in Nashville, TN

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.

Design and operate Alpaca’s scalable data platform on GCP, including lakehouse infrastructure, Kubernetes-based deployments, streaming and CDC pipelines, batch ingestion, BI access, cataloging, monitoring, and governance. Build infrastructure as code with Terraform and Ansible, operate distributed query engines and Apache Iceberg, maintain reliability practices, and collaborate with DevOps and analytics teams to support rapidly evolving data requirements.

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.

Leads commercial business intelligence strategy, Power BI reporting, dashboards, analytics, data governance, CRM optimization, and sales process improvement. Manages two direct reports and partners with commercial, finance, and operational leaders to improve revenue performance, forecasting accuracy, data quality, and commercial effectiveness. Oversees sales incentive compensation analytics and cross-functional system transformation initiatives. The role is fully remote with 10% overnight travel.

Leads the Business Intelligence and Revenue Analytics function, balancing team management with hands-on analysis. Develops dashboards, KPI frameworks, forecasts, and reporting for Sales, Marketing, Revenue Operations, and executives. Partners with Data Engineering on data models, pipelines, governance, and quality. Translates business needs into analytical solutions, delivers actionable insights, manages the analytics roadmap, prioritizes initiatives, and coaches a small team.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy, delivers executive dashboards and operational reporting, establishes KPI and governance standards, builds semantic models and curated datasets, and drives self-service BI adoption. Partners with Engineering, Product, Finance, Operations, Customer Success, and executives to translate business needs into trusted analytical solutions while developing talent and prioritizing analytics initiatives.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy; delivers executive dashboards, KPI scorecards, operational reporting, semantic models, and self-service BI. Establishes data governance and metric standards, ensures data quality, partners with Engineering, Product, Finance, Operations, and executives, and translates business questions into actionable analytical solutions. Mentors analytics talent and drives prioritization, adoption, and measurable business outcomes.

An 11-week paid actuarial internship supporting product development, financial management, risk management, and actuarial analytics. Responsibilities include compiling and validating data, conducting actuarial studies and experience analyses, performing calculations and reserve analyses, preparing financial projections and management reports, documenting methodologies and assumptions, and collaborating with business partners. Interns also receive mentorship, technology training, leadership exposure, and presentation-development opportunities.

Designs and maintains scalable data architecture, Snowflake warehouses, ETL/ELT pipelines, dimensional data models, and governance processes. Partners with business stakeholders to deliver insights for pricing, inventory, customer segmentation, and marketing optimization. Builds reliable analytics datasets and dashboards, integrates data tools, monitors data quality, and ensures compliance within the regulated cannabis industry.

Designs and builds production data systems, pipelines, database schemas, analytical models, and internal platforms. Responsibilities include writing tested code, optimizing queries and storage, controlling infrastructure costs, enforcing CI/CD, and implementing data testing, monitoring, and alerting. The role also develops AI and LLM-backed data use cases, including retrieval pipelines, embeddings, vector storage, evaluation harnesses, and agentic workflows.