Top Data & Analytics Jobs in Nashville, TN

Build and maintain scalable GTM data pipelines, marts, semantic models, and dashboards supporting headcount planning, quota attainment, pipeline, and sales effectiveness. Partner with GTM analysts and stakeholders to establish reliable metrics, enable data tools, document systems, and develop AI-powered natural-language data querying capabilities. Translate complex data concepts for executives and engineers while ensuring high-quality, maintainable data products.

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

Provides analytical support and consulting to clinical and business stakeholders. Queries internal and external data sources, develops insights and dynamic dashboards, and advises senior leaders. Translates business cases into customer or partner execution while collaborating across teams and championing initiatives. Requires strong healthcare or statistical analysis knowledge, technical proficiency in SQL, R, Python, and data visualization tools, plus strong communication and presentation skills.

Develop and maintain Power BI dashboards, DAX measures, SQL data models, and enterprise reports. Integrate ERP, project, and business systems through APIs; manage data transformations, quality, governance, and pipelines. Analyze trends and KPIs, support AI-enabled reporting and workflow automation, and collaborate with project, finance, technology, and operations teams to translate requirements into reporting solutions. Provide user support and training for analytics platforms.

Leads the design, engineering, reliability, security, and evolution of the enterprise data platform. Manages data engineers and database administrators while contributing hands-on to architecture, pipelines, databases, troubleshooting, performance tuning, governance, and production support. Owns platform roadmaps, DataOps standards, monitoring, disaster recovery, capacity, vendor services, and incident resolution. Partners with architecture, analytics, security, infrastructure, data science, and business teams to deliver scalable, governed, and dependable data products.

Leads the design, development, governance, and productization of enterprise data models, pipelines, data products, and ontologies. Builds machine-learning-ready datasets, implements security and lineage controls, optimizes Databricks and Delta Lake environments, establishes data-product standards, collaborates with architects and data scientists, and mentors engineering talent. The role also defines product roadmaps, service levels, usage metrics, and continuous-improvement processes for enterprise data assets supporting AI agents, analytics, and applications.

Leads product metadata strategy, governance, taxonomy, standards, and quality across publishing products and sales channels. Designs data models, validates records, manages ONIX feeds and identifiers, improves discoverability, coordinates corrections, and integrates rights information. The role collaborates with IT, marketing, sales, editorial, distribution partners, vendors, and industry standards organizations while guiding cross-functional adoption without direct supervisory authority.

Lead the architecture and implementation of scalable GCP and Databricks data lakehouse platforms. Design batch and real-time pipelines, data models, governance, cataloging, security, and performance strategies. Act as a technical lead and trusted client advisor while mentoring engineers, guiding architecture decisions, conducting proofs of concept, and supporting hands-on troubleshooting and delivery.

Manages data engineering teams and leads architecture, design, and delivery across the data lifecycle. Builds scalable data infrastructure, pipelines, warehouses, and ETL processes using cloud and big-data technologies. Responsibilities include data modeling, system optimization, automation, analytics, predictive modeling support, and collaboration with business intelligence and data warehouse teams. The role also evaluates business needs, interprets trends, develops prototypes, and communicates analytical results to stakeholders.

The Business Systems Analyst bridges business and IT by documenting objectives, eliciting and validating requirements, analyzing systems and processes, supporting automation, conducting data analysis, and developing recommendations and reports. The role collaborates with project stakeholders, creates and executes test plans, supports users through training and documentation, and ensures solutions align with business strategies.