Top Data & Analytics Jobs in Palm Bay, FL

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.

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.

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.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Manages a data engineering team responsible for scalable, reliable data pipelines, infrastructure, and analytics tooling. Provides mentorship, performance management, and technical leadership while coordinating with product, analytics, finance, compliance, engineering, and regulators. Prioritizes cross-functional projects, supports data architecture and governance, ensures performance and reliability, and operates within strict regulatory and audit requirements.

Senior Database Analyst/Administrator responsible for database architecture, administration, performance, security, data modeling, warehousing, ETL, migration, and data integrity. Develops SQL Server database objects, dimensional models, enterprise data marts, BI dashboards, and Splunk monitoring reports. Collaborates with stakeholders to translate business needs into technical requirements, supports Agile development, conducts code reviews, and implements cloud and hybrid-cloud database solutions.

Design, develop, and optimize scalable Databricks data pipelines using PySpark, SQL, Spark, and Delta Lake. Build workflows, ingestion and transformation processes, data quality checks, monitoring, and CI/CD automation. Optimize distributed workloads, configure Databricks compute, support cloud governance and access controls, troubleshoot production issues, and collaborate with technical and research stakeholders to deliver secure, reliable analytical datasets.

Owns lead and account data quality across the sales pipeline. Responsibilities include deduplicating and enriching CRM records, defining lead quality and routing standards, maintaining account structures, resolving data escalations, evaluating enrichment vendors, and assessing AI for quality assurance and anomaly detection. Partners with sales leadership to build scalable workflows and validation processes using CRM tools, SQL, spreadsheets, and potentially Python.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Own the company’s data function by designing and optimizing Snowflake architecture, pipelines, integrations, data models, BI dashboards, metric definitions, governance, and data-quality standards. Partner with leadership and cross-functional teams to translate operational needs into trusted data products. Automate recurring reporting, troubleshoot ingestion issues, perform ad hoc analysis, and establish scalable analytics practices as the first dedicated analytics hire.

Owns enterprise workforce intelligence and employee listening strategy. Analyzes employee sentiment, workforce trends, talent, skills, organizational effectiveness, and work data to identify risks and opportunities. Develops dashboards, analytical methodologies, AI-enabled insight products, and self-service resources. Partners with HR leaders and data owners to translate complex quantitative and qualitative findings into actionable recommendations for workforce planning, succession, organization design, automation, and capability decisions.

Design, develop, and publish advanced interactive Power BI reports and dashboards; define data structures and ETL needs; build analytics models using Microsoft BI stack (Power BI, SSAS/AAS, dataflows); use DAX and SQL to implement complex logic; collaborate with data engineering and business partners; mentor junior developers and performance-tune reports.

Supports loyalty and retention analytics through A/B test management, KPI tracking, recurring dashboards, and performance reporting. Monitors churn, winback, cancellation, and loyalty metrics; identifies trends, risks, and opportunities; and translates findings into actionable recommendations. The role also manages loyalty merchandise planning and replenishment, collaborates with Data Science and program owners, coordinates analytics requests, and prepares MBR/QBR materials.