Top Remote Data & Analytics Jobs in Miami, FL

Leads enterprise information architecture, business intelligence, and data warehouse strategy and delivery. Oversees BI and data warehouse teams, establishes roadmaps and governance, mentors technical staff, manages project priorities, and ensures high-quality implementation. Designs enterprise data models, datamarts, metadata, ETL processes, reporting strategies, and integration artifacts. Partners with business and technology stakeholders to align data solutions with strategic goals, improve adoption, track value, and drive continuous improvement.

Lead live DeFi education sessions, support approximately 400 students per six months, explain complex crypto concepts simply, research crypto projects, write DeFi articles, create video content, and conduct trading, technical, and on-chain analysis to evaluate investments and identify opportunities.

Lead and mentor data engineering and DBA teams while driving GCP-based streaming and batch data platform initiatives. Oversee BigQuery, dbt, Apache Flink or Dataflow, data quality, testing, observability, governance, reliability, and cloud cost optimization. Remain hands-on with coding, code reviews, architecture, and complex system problems while aligning data infrastructure with business and product goals. Champion AI-assisted engineering and automation across the platform.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Leads the organization’s data strategy, analytics, and measurement capabilities. Advises enterprise clients on attribution, incrementality, marketing mix modeling, customer acquisition, and lifetime value. Develops measurement frameworks, dashboards, reporting products, and analytics tools while partnering with strategy, sales, client services, and AI teams. Builds internal data literacy, coaches talent, supports commercial growth, and represents the company as an external thought leader in partnership marketing measurement.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

The Business Analyst will support government projects by documenting requirements, creating process maps, and improving service delivery through collaboration and innovative content development.

Design, build, and operate scalable batch and real-time data pipelines and infrastructure. Own end-to-end data products, establish observability and data quality, troubleshoot production issues, document architectures and runbooks, and partner with analytics, ML, and product teams to deliver reliable, self-serve data solutions.

Lead end-to-end Palantir Foundry implementations: architect Ontologies, design pipelines, and build Workshop/Slate applications. Translate business goals into technical roadmaps, drive adoption, mentor juniors, support US business development, and travel to client sites as needed.

Own analytics as an internal data product across GTM, People, Finance, and related functions. Translate ambiguous business questions into self-service data solutions, deliver executive-ready narratives, manage stakeholder priorities, and guide data-driven decisions. Serve as a marketing analytics subject matter expert across attribution, campaign measurement, lead tracking, funnel analysis, predictive modeling, and experimentation. Use SQL, modern data-stack tools, BI platforms, and AI-assisted modeling to deliver actionable insights.