Top Senior Data & Analytics Jobs in Orlando, FL

The Senior Manager leads Power BI reporting and analytics functions, overseeing a team and ensuring standardized, scalable reporting solutions while managing transition to Microsoft Fabric.

Develop and lead data ingestion, transformation, and distribution pipelines using SQL, Snowflake, Python, and related technologies. Oversee offshore data engineers, conduct code reviews, facilitate Agile ceremonies, and manage delivery timelines. Design batch and real-time pipelines, implement data validation and testing frameworks, optimize queries, troubleshoot bottlenecks, and ensure data integrity. Collaborate with architects, product owners, administrators, and business analysts to translate requirements into technical solutions.

Develops and deploys scalable big data platforms, ETL pipelines, data warehouses, and data architectures. Designs, codes, tests, documents, and optimizes data solutions; troubleshoots data issues; improves reliability, efficiency, and quality; and collaborates with developers, architects, analysts, scientists, and business teams.

Lead the architecture and strategic direction of an enterprise data platform across ingestion, storage, processing, governance, and consumption. Establish standards for data modeling and lifecycle management, guide scalable lakehouse and streaming architectures, and partner with engineering, analytics, ML, and business teams. The role requires hands-on expertise with major data platforms, Spark, Flink, or Kafka, plus experience delivering governance, lineage, catalogs, cloud infrastructure, and large cross-team data platform initiatives.

Leads operational analysis, reporting, dashboards, automation, and strategic planning support for enterprise initiatives. Builds solutions using Python, Power BI, Alteryx, and UiPath; applies AI to improve workflows and decision support; presents insights to senior stakeholders; and drives process improvements and multi-year cross-functional projects.

Designs, builds, and operates scalable cloud data platforms across Azure, Microsoft Fabric, and AWS. Develops Python ETL/ELT pipelines, containerized Azure Container Apps Jobs, data warehouses, dimensional models, and integrations between on-premises and cloud systems. Responsibilities include infrastructure as code, CI/CD, monitoring, security, cost optimization, documentation, stakeholder collaboration, and mentoring junior engineers.

Analyze customer lifecycle and Customer Success data to measure attribution, campaign performance, product adoption, retention, and revenue impact. Build multi-touch attribution models, integrate digital engagement data with Gainsight and CRM events, clean and unify datasets, segment audiences, identify journey bottlenecks, and create Tableau or Looker dashboards. Partner with Campaign Strategy, Product Insights, and CS Operations teams to deliver actionable recommendations and improve automated and human customer interventions.

Design, build, and operate high-throughput Go services and data pipelines powering a cybersecurity data lake. Own bronze, silver, and gold layers, including ingestion, enrichment, partitioning, compaction, schema evolution, and performance optimization. Translate threat intelligence workflows into reliable production systems, collaborate across teams, participate in on-call operations, and mentor engineers. The role requires distributed-systems expertise, experience with open table and columnar formats, object storage, ClickHouse, PostgreSQL, and large-scale datasets.

Leads healthcare data analysis, reporting, dashboard development, forecasting, and data-quality processes. Analyzes claims, utilization, cost, pharmacy, and financial data to identify trends and support cost-containment and business decisions. Develops SQL database objects, translates stakeholder requirements, supports regulatory reporting, improves analytics workflows, and manages projects. Provides mentoring, peer review, documentation, and cross-functional guidance.

Owns data infrastructure, datasets, dashboards, predictive models, and AI-enabled workflows for JLL’s national industrial real estate platform. The role supports investor and occupier business development through analytics, market research, supply-chain mapping, reporting, presentations, and executive insights. Responsibilities include coordinating cross-functional teams, improving data protocols, evaluating technology platforms, automating repetitive analysis, supporting pursuits, and communicating analytical priorities to leadership.