Top Senior Level Data & Analytics Jobs in Miami, FL

The Application Systems Analyst aids businesses in achieving their goals by evaluating, designing, and developing full stack application systems. Responsibilities include developing applications on FileMaker, consulting with management, creating application specifications, overseeing implementation, diagnosing errors, and managing reported incidents.

The Data Analytics Architect leads the design and administration of a federal customer’s data analytics suite. Responsibilities include working primarily with Splunk and Cribl in cloud environments, optimizing data storage configurations, and collaborating with teams on security content requirements for SOC operations.

The Data Engineer is responsible for designing and maintaining data structures, ensuring accuracy and accessibility of data, assessing existing data architecture, supporting BI reporting needs, and creating quality standards for data integrity, while working with clients to meet their data management needs.

The Investigative Support Analyst provides support for criminal and civil investigations by analyzing business records, tracing illegal activity proceeds, and presenting findings in reports. Responsibilities include data mining, preparing detailed reports, assisting Postal Inspectors, and ensuring completion of tasks within set timeframes.

The Workday Lead Analyst will design, develop, and maintain Workday integrations and reports, support HR and Finance functions, and ensure the smooth operation of Workday systems. Responsibilities include system maintenance, report development, user training, and participation in project management.

As a Data Analyst III at Calendly, you will leverage data visualization and analytics to support cross-functional reporting and ad hoc analyses. Your role includes building dashboards in Tableau and Hex, performing complex analyses using SQL, Python, or R, and defining business metrics in dbt. You will also communicate insights effectively to promote data-driven decision-making across the company.

Lead the Data Science team, developing AI models and statistical systems while collaborating with cross-functional teams. Drive research and data strategies that enhance product effectiveness and farmer profitability.