Top Analysis Reporting Jobs in Charleston, SC

Designs and maintains enterprise data architecture, including data lakes, warehouses, integrations, migrations, orchestration, and data management protocols. Partners with architects, DBAs, BI teams, product leaders, and business stakeholders to support analytics and data science. Requires deep experience with cloud data environments, Azure SQL, Microsoft Fabric, Spark, Hadoop, PySpark, SparkSQL, security protocols, and enterprise data integrations.

Leads enterprise data strategy, lakehouse delivery, data products, and data and AI governance. Establishes platform standards, data ownership, quality, lineage, lifecycle, privacy, and regulatory controls. Builds governance operating models for AI development and monitoring, manages platform teams and partners, oversees external data acquisition, and reports risk, maturity, and compliance to executives, clients, and auditors.

Maintain and optimize Oracle databases supporting federal Web/Oracle systems in AWS. Responsibilities include database configuration, performance monitoring, backups and restoration, replication, schema management, release and testing support, firewall coordination, STIG compliance, audit support, and developing infrastructure-as-code solutions. The role requires Oracle DBA, PL/SQL, AWS RDS, database replication, and security compliance experience, along with a Secret clearance and Security+ CE or CCNA Security certification.

Lead architecture and execution of Grafana's marketing data stack and analytics practice. Build forecasting, predictive, and causal models, design BigQuery schemas, deploy agentic AI and automated pipelines, partner with GTM leadership, and deliver executive-grade insights to drive demand generation and ROI.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Build and operate batch and streaming data pipelines on Google Cloud for analytics and machine learning. Ingest, transform, validate, and curate datasets in BigQuery; implement data quality, governance, security, monitoring, Terraform infrastructure, and CI/CD. Provide technical direction, lead code reviews, and document data processes. The role requires cloud data engineering experience, technical team leadership, strong SQL and Python skills, and eligibility for a federal Public Trust investigation.

Performs treasury finance operations, including loan sales, data analysis, reconciliation, and financial controls. Automates recurring workflows using SQL, Python, Excel, and AI tools; maintains and modernizes data pipelines; investigates discrepancies; and communicates insights to technical and business stakeholders. Serves as a subject matter expert on loan data and finance processes while supporting fraud prevention and financial governance.

Leads marketing measurement strategy through geo holdout and incrementality testing, forecasting, experimentation, and statistical analysis. Partners with Marketing, agencies, and Data Science to guide channel budgets and campaign decisions. Queries large-scale data using SQL and Python in Databricks and BigQuery, develops measurement models, automates analyses with AI tools, and mentors analysts while providing technical leadership.

Lead pre-sales technical engagements to design and optimize scalable cloud lakehouse data platforms (Snowflake/Databricks). Provide architecture reviews, ETL/ELT pipeline design, governance and AI-ready data foundations, support services sales, and translate technical tradeoffs into actionable recommendations for engineering and executive stakeholders.

Build and maintain scalable data pipelines, infrastructure, data models, and APIs using Python, SQL, Airflow, Snowflake, dbt, Terraform, and cloud services. Ensure data quality, security, observability, and reliability while collaborating with analysts, product managers, and engineering teams. Own aspects of the FastAPI data service, including design, deployment, monitoring, and performance. Handle sensitive healthcare data in compliance with governance standards.