Top Senior Analysis Reporting Jobs in Charleston, SC

Leads end-to-end data architecture, ETL pipelines, data models, quality frameworks, monitoring, and BI platform operations. Manages Tableau infrastructure, drives project plans and agile sprint delivery, establishes AI-enabled analytics capabilities, and partners with cross-functional stakeholders. Coaches and manages data engineering team members while ensuring data availability, accuracy, security, documentation, and continuous improvement.

Leads Ford’s multi-touch attribution team and enterprise marketing measurement capability. Responsibilities include managing eight employees, vendor relationships, data pipelines, analytics intake, taxonomy governance, data quality, statistical validation, causal inference, dashboards, and reporting. The role uses GCP, Python, and SQL to automate attribution workflows, evaluates marketing effectiveness, oversees budgets and contracts, partners with media agencies, and communicates insights to technical and business stakeholders. It also promotes AI/ML and generative AI adoption while ensuring privacy, policy compliance, and alignment with Marketing objectives.

Own and build Underdog’s regulatory reporting data platform, including dbt models, resilient pipelines, automated validations, monitoring, and reporting roadmaps. Partner with regulators, engineering, product, compliance, and leadership; lead audits, investigations, root-cause fixes, data governance, and on-call operations. WOOF WOOF.

Performs advanced data extraction, statistical analysis, modeling, forecasting, and visualization using enterprise data sources. Builds and maintains Power BI dashboards and Snowflake data models, supports data governance and regulatory reporting, and translates business needs into actionable insights. Serves as a trusted analytics consultant, leads reporting and analysis projects, presents findings to technical and non-technical stakeholders, and improves reporting through automation and standardized methodologies.

Design, build, and operate production data pipelines using Python, Spark SQL, and Airflow. Canonicalize healthcare and customer data into trusted internal models, optimize distributed processing, enforce schemas, and implement quality checks and observability. Support customer onboarding, streaming pipelines, troubleshooting, on-call operations, and platform best practices while collaborating with product, analytics, engineering, data science, and customer teams.

Leads Point C’s enterprise analytics strategy, data platforms, governance, reporting, and insights delivery. Builds trusted analytics for brokers, employers, sales, operations, finance, and clinical teams; oversees data integration, quality, standardization, and acquisition-related analytics. Develops a scalable agile analytics organization and aligns roadmaps, metrics, and delivery standards with business growth and executive decision-making.

Administer and optimize production and non-production databases for a large-scale VA data migration. Responsibilities include installation, patching, performance tuning, backup and recovery, security, AWS database provisioning, data conversion, validation, troubleshooting, high availability, disaster recovery, and technical documentation. The role collaborates with developers and analysts across on-premises and AWS environments while ensuring database availability, integrity, and security.

Design, build, and own business-critical data infrastructure, including AWS Glue and Spark pipelines, cloud warehouse or lakehouse systems, orchestration, and Tableau BI platforms. Define event-driven contracts, data models, schemas, observability, and batch or streaming architectures across multi-tenant, multi-region environments. Collaborate across producer and consumer teams while owning production data infrastructure and outcomes end to end.

Lead a BI engineering team, overseeing dashboards, data models, SQL/dbt transformations, ETL pipelines, Airflow DAGs, data warehouses, CI/CD, governance, and quality standards. Partner with stakeholders to define reporting requirements, conduct advanced analyses, manage Agile projects, and develop data strategy. Mentor team members and support production deployments. This fully remote role requires travel to Denver for five business days each quarter.

Analyze and model property catastrophe reinsurance treaties using catastrophe modeling platforms. Prepare and validate exposure data, execute models, interpret risk metrics, develop scenarios, and identify portfolio risk drivers. Support underwriting, actuarial pricing, placement, renewals, and management decisions through clear reporting. Participate in model validation, calibration, research, and development while collaborating with underwriters, actuaries, and other stakeholders.