Top Analysis Reporting Jobs in Charleston, SC

Lead global data governance strategy and operating model, establish enterprise data management/MDM and data certification practices, build and lead the global governance function and steward program, drive change management and adoption across business lines, partner with cross-functional teams to resolve data risks and embed governance into workflows, and deliver measurable outcomes against the governance roadmap.

Senior technical leader responsible for designing and implementing scalable Databricks/Azure data architectures, building high-scale pipelines, embedding across teams to unblock delivery, mentoring engineers, and defining engineering standards and best practices for enterprise data platforms.

Lead enterprise sales forecasting, pipeline governance, and KPI reporting to drive growth performance. Own forecast reviews, executive reporting, sales compensation tracking, and data-driven insights. Partner cross-functionally with Sales, Finance, Growth Ops, and Market Leaders to improve conversion, planning accuracy, and revenue outcomes, while supporting systems, data quality, analytics automation, and performance frameworks.

Design and recommend Snowflake-based analytic architectures, lead implementation work streams, advise engineering teams on data cloud migrations, mentor junior staff, support presales, and leverage AI to optimize data warehouse and lake solutions across project lifecycles.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Design and deliver executive-ready Power BI reports, dashboards and agentic experiences. Build semantic models and self-service analytics, apply DAX, Power Query and Fabric notebooks, perform data exploration with SQL/KQL, and drive AI-enabled automation. Collaborate with data engineering to influence ingestion and transformation, translate business strategy into data solutions, and ensure performance, reliability, and scalability of reporting assets.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Design, build, and maintain scalable dbt transformation pipelines and dimensional data models on Databricks. Partner with data engineering and stakeholders to deliver trusted silver/gold datasets, implement data quality tests and monitoring, enable self-service semantic layers, and enhance LLM-driven tooling to accelerate analytics and automation.

Design, build, and maintain large-scale data pipelines, ETL/ELT processes, and data models. Collaborate with analysts, architects, and data scientists to deliver BI solutions, optimize performance, support production systems, and mentor team members. Implement cloud and on-prem data architectures, CI/CD practices, and tooling to enable data-driven decision-making across the business.

Design, build, and maintain data pipelines, ETL/ELT processes, and data warehouses. Develop complex data models, tune SQL/PLSQL, support production BI/reporting, and collaborate with analysts and architects to deliver scalable analytics solutions. Mentor teammates and participate in agile delivery and production support.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Build and operate ingestion and transformation pipelines, model and test core warehouse data, enable analytics and reporting, and maintain ML data infrastructure feeding matching and recommendation models. Partner with Engineering, Product, and Data Science to ensure reliable, documented, and trusted data at scale.

The Solutions Analyst delivers reporting and operational outputs, analyzes datasets, resolves issues, maintains solution components, and collaborates with teams to improve efficiency.

Design, build, and operate scalable PostgreSQL databases and cloud-native data infrastructure. Build and maintain ETL/ELT pipelines, optimize query and server performance, ensure high availability and disaster recovery, improve observability, troubleshoot production issues, guide schema and application design, evaluate database technologies, and mentor junior engineers to support reliable, secure data-driven applications.