Top Remote Data & Analytics Jobs in Jacksonville, FL

Design and build Power BI reports and SSRS reports, write advanced SQL to extract and validate data, create scalable data models, investigate trends, automate reporting processes, and collaborate with business partners to translate requirements into usable analytics solutions.

Designs, deploys, and supports healthcare data acquisition, integration, transformation, and data quality solutions using enterprise and cloud technologies. Develops SQL assets, OMOP Common Data Model transformations, testing processes, documentation, and AI data pipelines. Manages projects, resolves escalated incidents, mentors data engineers, supports training, and collaborates with analysts, vendors, clients, and technology teams.

Build and maintain performance dashboards, KPIs, and data frameworks for revenue operations. Analyze funnel performance and program effectiveness, translate complex data into leadership insights, automate recurring reporting, and perform SQL-based data wrangling and transformations. The role partners with cross-functional, engineering, and data science teams to improve measurement, resolve data issues, and support strategic business decisions.

Own paid social measurement and analytics across brand, consideration, and performance campaigns. Execute Conversion Lift and Brand Lift Studies, design geo-randomized experiments with data science, build KPI dashboards, evaluate creative and audience performance, and recommend budget and strategy changes. The role requires advanced SQL and Python or R, causal inference expertise, scalable reporting, and the ability to communicate insights to senior marketing leaders.

Implement, QA, and document tag management and data-layer specs across GTM, GA4, server-side pipelines, Shopify, and native apps. Collaborate with product and engineering to ensure tracking, pixel integrity, attribution, and experimentation event fidelity; support monthly audits, consent enforcement, and maintain centralized solution design documentation.

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.

Design, build, and maintain Data Vault 2.0 data warehouse and Power BI solutions. Develop ETL pipelines, data models, reusable datasets, and data governance. Perform profiling, cleansing, migrations, and collaborate with infrastructure teams to optimize data delivery, automation, and reporting.

Lead infrastructure analytics for compute, storage, and networking: design scalable data pipelines, define core metrics, build dashboards and APIs, ensure data quality and governance, drive instrumentation fixes, and advise executives on capacity, utilization, and readiness.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Lead delivery of enterprise data governance, MDM, and modern data-platform components including Snowflake, CDC pipelines, schema-first contracts (JSON Schema/Avro/Protobuf), data catalog and PII classification, CI/CD schema management, AWS data services, and day-to-day leadership of an offshore delivery team.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Perform data conversions and imports from diverse sources (text, PDFs, Excel). Clean, validate, reconcile, and audit employee demographics and payroll history using SQL and automation tools. Troubleshoot issues, document processes, and collaborate with implementation stakeholders to deliver accurate, timely conversions and improve automation.