Top Data & Analytics Jobs in Palm Bay, FL

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Analyze and manipulate large datasets supporting energy modeling and SEM programs. Review data before and after modeling, maintain standardized templates and databases, integrate data into statistical software, quality-control models and reports, and create work instructions. The role also involves automating data processing, troubleshooting Visual Basic and Excel tools, managing Smartsheet data, supporting benchmarking reports, and collaborating with internal teams and occasional clients.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Develops and automates complex sales reports and dashboards using Power BI, SQL, SSRS, SSIS, Excel, and related tools. Performs data transformation, cleansing, modeling, analysis, reconciliation, and integrity controls. Serves as a reporting subject matter expert, supports partners and leadership, resolves reporting escalations, mentors analysts, and contributes analytics to revenue-growth initiatives.

Develop and maintain data engineering solutions using Informatica Data Management Cloud, Control-M, Snowflake, and SQL. Responsibilities include sourcing, transforming, cleansing, ingesting, analyzing, and visualizing data; building automated workflows and scalable ETL processes; supporting data architecture and deployments; and delivering reusable code for large datasets. The role requires collaboration with technical and business partners, troubleshooting, mentoring, and managing multiple priorities.

Manages analysts and leads marketing analytics for digital and offline media channels. Develops measurement plans, experiments, dashboards, campaign reports, and optimization insights using marketing data. Presents recommendations to clients, supports media planning and new business pitches, ensures reporting accuracy, and advances analytics workflows through AI-enabled tools and automation. Requires strong web, social, SEM, dashboard, statistical programming, and marketing measurement expertise.

Develop Power BI dashboards, reports, data models, and visualizations, while building Power Apps applications and Power Automate workflows to automate business processes. Gather requirements from stakeholders, integrate Dataverse, SQL Server, SharePoint, and other data sources, troubleshoot solutions, optimize reporting performance, analyze KPIs, and present insights to management. Provide ongoing support to business and finance stakeholders.

Manages client, compliance, and performance reporting across healthcare programs using eligibility and claims data. Leads reporting analysts while remaining hands-on with advanced SQL, dashboards, data crosswalks, validation, reconciliation, root-cause analysis, and data-quality monitoring. Partners with data engineering and clients to resolve upstream issues, establish reporting standards, and guide the analytics roadmap.

Architect and maintain NetBrain’s first cloud data warehouse, ELT pipelines, transformation layer, semantic models, and BI foundation. Own data quality, governance, lineage, access controls, and curated models supporting product usage, customer adoption, account health, and go-to-market reporting. Partner with stakeholders to establish reliable metrics and a standardized source of truth, while supporting AI-assisted analytics and natural-language reporting use cases.

Build and operate scalable data infrastructure and pipelines for video, imagery, telemetry, sensor, log, and mission data. Create searchable data lakes, curated and versioned ML datasets, labeling workflows, quality checks, lineage, monitoring, and reproducible dataset-generation processes. Partner with autonomy, perception, software, simulation, and field teams to support model training, evaluation, debugging, replay, and deployment workflows.