Top Analysis Reporting Jobs in Jacksonville, FL

Process, validate and QA large survey datasets; produce datasets, tables, codeframes and documentation; support weighting, testing and statistical analyses; learn and apply Python/R, automation and AI-assisted tools; improve automated processing workflows under senior guidance.

Senior data processing analyst responsible for end-to-end survey data processing: specifications, weighting, QA, documentation and deliverables. Produce datasets and tables, perform statistical tests, and modernise/automate workflows (Python/R, replace SPSS). Apply AI-assisted tools, act as technical lead for projects, and mentor junior analysts.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Analyze product performance metrics and user behavior to drive insights for product improvements. Collaborate with teams to develop reporting practices, A/B tests, and dashboards to inform strategy.

Own and QA high-impact retail data products: design and run QA, investigate and resolve complex data quality issues, collaborate with Insights and Engineering, improve automation and product reliability, and communicate methodology and limitations to clients.

Senior technical leader defining Subaru of America's enterprise data architecture strategy across platforms, integration, governance, analytics, and security. Shapes 3-5 year data strategy, drives architecture standards, enables AI/agentic workflows, leads cross-functional solutions, mentors teams, and represents SOA externally to advance data capabilities and compliance.

Analyze, integrate, clean, and model operational and technical data to produce dashboards, reports, and forecasts. Identify trends, lifecycle/status, risks, and noncompliant assets; support automation, data quality improvements, and decision-making across engineering and operations teams.

Design, build, and maintain interactive dashboards and visual products that translate complex operational and cybersecurity data into clear insights. Collect requirements, create mockups, automate analytics, and produce metrics for patching, vulnerability, and compliance to support executive and operational decision-making.

Lead SAP S/4HANA data migration activities: extract, map, transform, load, validate, and reconcile master and transactional data using BODS, Migration Cockpit, LSMW/BDC and HANA SQL. Support mock loads, cutover execution, defect remediation, and collaborate with functional owners to cleanse and correct source data.

Architect and scale a governed BI and analytics platform (Snowflake, dbt, Sigma) to deliver trusted, standardized KPI frameworks and semantic layers. Build high-quality data models, optimize SQL for large datasets, enable self-serve analytics, mentor engineers, drive governance and testing standards, and partner with Product, Data Science, Finance, and business teams. Promote AI-assisted tooling to accelerate analytics delivery and improve metric trust and reporting consistency.

Lead design and hands-on delivery of a next-generation data platform and pipelines (batch, ELT, near-real-time) powering BI, experimentation, and ML. Own platform architecture, data modeling, governance, observability, and mentor engineers while modernizing legacy systems and driving AI-first data engineering practices across cross-functional teams.

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.

As a Data Engineer, you will design and maintain data pipelines, support DoD systems, and ensure data quality and compliance.

Design, build, and optimize scalable cloud data pipelines and infrastructure. Maintain and refactor SQL and ETL processes, automate data workflows, ensure data quality/security, and troubleshoot complex issues. Provide technical leadership and mentor junior engineers while collaborating with stakeholders to translate requirements.