Top Senior Data & Analytics Jobs in Charleston, SC

Build and maintain enterprise data platform and ETL/ELT pipelines, design and deploy data models, ensure data quality and governance, integrate third-party sources, and support analytics and AI initiatives across the organization.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Serve as primary DBA SME bridging on-premises SQL Server to Microsoft Fabric. Design hybrid database architectures, implement cloud-based SQL services, establish Data Operations processes and SLAs, manage data integration, security controls, performance tuning, monitoring, and disaster recovery to support analytics and AI workloads.

Design, implement, and manage scalable multi-cloud data platforms and ELT pipelines (AWS/Azure). Build and optimize Snowflake data models, dbt transformations, and Airflow orchestration. Define data engineering standards, enforce governance and quality, collaborate cross-functionally, and mentor global/offshore teams.

Lead BI developer owning end-to-end reporting for marketing verticals. Build and standardize dashboards, model complex/third-party data (LookML), partner with Yield, Paid Media, and Account Management to deliver actionable analyses that optimize campaign performance, conversion, and revenue.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

The Data SME will provide strategic guidance on data management and analytics, ensuring data quality and governance while collaborating with global teams to improve data solutions.

The Senior Insights Analyst will analyze data to provide insights into the subscription economy, present findings, support reports, and manage projects while mentoring junior team members.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.