Top Data & Analytics Jobs

Leads enterprise reporting, data modeling, governance, reconciliation, and dashboard development across wealth management systems. Ensures data integrity and standardized KPI reporting while analyzing financial and operational trends. Partners with business, technology, operations, finance, and senior leadership to deliver actionable insights, improve reporting processes, support system transformations, and drive adoption of consistent reporting practices.

Leads enterprise data modeling, governance, reconciliation, and reporting across wealth management systems. Develops dashboards and KPI frameworks, ensures data integrity, analyzes financial and operational trends, and delivers executive insights. Partners with business, technology, operations, and finance teams to standardize reporting, support system transformations, improve automation, and drive data-informed decisions.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Leads Lennar’s third-party data analytics function and enterprise data strategy. Responsibilities include setting priorities, improving data infrastructure, overseeing data engineering and analytics practices, ensuring governance and security compliance, and partnering with senior leadership. The role designs scalable data architectures, integrates multiple data sources, develops dashboards and reporting solutions, applies advanced analytics and AI, and leads data projects and teams while mentoring staff and driving organizational data initiatives.

Performs complex data analysis for field operations and call centers to improve targeting, resource allocation, and ROI. Develops and validates reports, dashboards, and data models using Excel, SQL, and Power Query. Identifies trends and issues, evaluates analytical methods, and recommends practical business solutions. Supports performance measurement across operations, training, product launches, and related business functions.

Develop and maintain enterprise geospatial applications, web services, dashboards, geoprocessing tools, and automation using Python and Esri technologies. Integrate and administer geospatial systems, troubleshoot GIS applications, manage data gateways, and migrate legacy applications to AWS Cloud One. The role also requires ArcGIS administration, database experience, spatial data standards knowledge, technical communication, and support for Air Force GeoBase initiatives using Agile practices.

Designs and builds lakehouse data models, pipelines, data marts, semantic layers, and digital-twin integrations for power plant assets. Combines telemetry, financial, operational, maintenance, and reliability data using Azure and Databricks technologies. Develops visualizations and supports web-product delivery while collaborating with product managers, UX designers, software engineers, analysts, plant staff, and executives.

Leads end-to-end data and analytics architecture engagements, specializing in Microsoft Fabric platform design, implementation, modernization, migration, governance, integration, semantic models, reporting, performance, and cost optimization. Partners with clients and internal teams to translate business needs into scalable solutions, guides technical delivery, supports pre-sales pursuits, and mentors data professionals. The role is remote but requires travel four to six times annually and residence in an approved state.

Develop and maintain SAS programs for cleaning, linking, transforming, and analyzing large health insurance claims datasets. Create cohorts, analytic datasets, variables, descriptive statistics, and reports for health policy research. Collaborate with investigators, statisticians, clinicians, and senior programmers across projects involving maternal, child, and mental health. Support data quality checks, statistical analyses, meetings, manuscripts, and research reporting.

Build and maintain reusable analytical data products, canonical entities, data marts, semantic layers, and governed metrics across business domains. Establish modeling, documentation, quality, lineage, and change-management standards; improve data reliability, self-service analytics, and production governance. Partner with Data Platform, Trust, Data Science, Applied AI, and business stakeholders on orchestration, observability, access controls, feature tables, model outputs, and shared metric definitions. Remain hands-on with SQL, Python, testing, code reviews, documentation, and technical coaching.