Top Remote Data & Analytics Jobs in Palm Bay, FL

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Build and maintain web crawling and scraping pipelines to collect, transform, and deliver third-party healthcare data. Research sources, assess feasibility, implement extraction strategies, test for quality, and maintain scrapers when sources change. Participate in weekly standups and initial fundraising activity.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Conduct quantitative and qualitative research, analyze complex business scenarios, gather requirements, and synthesize stakeholder perspectives into actionable recommendations. Evaluate data using tools such as Excel or SQL, identify process improvements, and produce clear reports, memos, business cases, and documentation. Collaborate with stakeholders through written communication and contribute analytical content to help train AI systems.

Build and operate event-driven data pipelines processing healthcare claims data for fraud, waste, and abuse detection. Operationalize validated fraud signals, maintain alert delivery and partner dashboards, monitor pipeline reliability, and collaborate with data architects, scientists, and investigative teams. The role requires production-scale pipeline engineering using AWS, Snowflake, Python, and SQL in a fully remote environment.

Design and deliver end-to-end BI architecture, dashboards, self-service reporting, and predictive analytics. Integrate analytics into the CMM application, enforce data governance, ensure performance SLAs, support AI/ML solutions, and collaborate with stakeholders to translate business requirements into scalable reporting and metadata processes within a regulated environment.

Supports government program data collection, reporting, analysis, forecasting, visualization, and dashboard development. Builds automated reporting solutions, data models, databases, and presentations; performs statistical analysis and interprets findings for agency leadership. Collaborates with federal stakeholders, contractors, and domain experts to improve data collection, identify performance indicators, provide technical support, and train field staff on data tools. The role is remote, with potential future onsite work in Washington, DC.

Own and evolve UJET’s data platform, including MySQL CDC replication to BigQuery, dbt transformations, Terraform infrastructure, pipelines, data quality, observability, and Looker models. Build reliable, analytics-ready datasets and trusted metrics for internal and customer-facing reporting. Partner with Analytics, Finance, Product, and Engineering to deliver scalable data solutions, improve platform reliability, optimize performance and costs, and establish development standards and guardrails.

Designs and maintains end-to-end data solutions, including ETL/ELT pipelines, BigQuery platforms, APIs, semantic data layers, and data catalogs. Builds data quality monitoring, governance, security, and access controls while collaborating with analytics, product, engineering, and business teams. Requires strong Python, Kotlin, Java, SQL, API development, cloud data engineering, testing, and reliability experience.

Build and operate batch and near-real-time data pipelines, semantic models, certified measures, APIs, and serving infrastructure for AI-powered decision systems. Responsibilities include data quality, observability, lineage, governance, CI/CD, infrastructure as code, performance optimization, model scoring pipelines, and AI telemetry. Partner with data scientists and business stakeholders to productionize models and deliver reusable, documented data platform capabilities.

Supports public health data extraction, management, quality assurance, cleaning, validation, harmonization, documentation, and statistical and qualitative analysis. Develops analytic datasets and evaluates program implementation, reach, fidelity, dose, adaptation, and outcomes. Integrates mixed-methods data, interprets findings, prepares technical memoranda, reports, presentations, tables, and figures, and communicates recommendations to program stakeholders. The role also uses Microsoft Office and CDC administrative systems and requires obtaining and maintaining customer clearance.

Supports survey data deliverables, crosstabs, data cleaning, open-ended coding, analysis, top-line reporting, and quality control. Validates datasets against ISO 20252 standards, tests surveys, develops data and analysis plans, and identifies findings and risks. Provides technical guidance to data-processing staff, coordinates project timelines, and uses research platforms including Qualtrics, SPSS, JMP, and QMOB.

Designs and maintains scalable data architecture, warehouses, ETL/ELT pipelines, and data platforms. Responsibilities include ensuring data quality, integrity, governance, accessibility, reliability, and performance; supporting customer onboarding and analytics tools; contributing to architecture and engineering best practices; troubleshooting complex data issues; and participating in on-call rotations. The role collaborates with engineering, product, solutions, business intelligence, and other cross-functional teams in healthcare and social care data environments.