Top Remote Data & Analytics Jobs in Charleston, SC

Own and build scalable analytics models, metric definitions, and dashboards (customer-facing and internal). Partner with engineering to design data flows and instrumentation (BigQuery, S3, PostHog). Translate stakeholder needs into analytics plans, triage requests, and surface insights via Looker/Observable. Set analytics stack direction and ensure data quality.

Lead a data engineering team building and operating NPR's data warehouse, pipelines, BI, and personalization systems. Responsibilities include people leadership, hiring, cross-functional collaboration, Agile delivery, technical design and code review, automation for developer experience, incident response, and vendor management.

Lead collection, integration, analysis, and transformation of encounter data to improve submission accuracy, compliance, and operational performance. Build scalable analytics and automation using Python, SQL, Databricks, and Power BI; perform root-cause analysis, translate business needs, optimize workflows, and mentor team members.

Analyze business questions using SQL and Excel, build dashboards and reports, synthesize findings into clear presentations, and deliver actionable insights to senior stakeholders to drive strategy.

Develop and lead healthcare analytics and BI solutions for HIS products: design, code, and deliver enterprise-scale applications and dashboards, work with AWS data services and BI tools, support product development and troubleshoot reporting issues for global customers.

Lead design, coding, and delivery of HIS analytics and reporting solutions. Build enterprise-scale applications and dashboards, collaborate in agile teams, support global customers, troubleshoot data/reporting issues, and integrate AWS data services with BI tools to transform raw data into actionable insights.

Design, develop, and implement ETL/BI and metadata/cataloging solutions. Lead data governance and data quality programs, build metadata catalogs, profile and remediate data issues, collaborate with stakeholders to define business rules and metrics, and support data stewardship and governance activities.

Serve as the technical owner for customer-facing data workflows and integrations: build pipelines, write SQL and Python scripts, deploy AI-powered workflows, manage APIs and Snowflake ingestion, and translate repeatable solutions into product requirements while supporting customer success and internal engineering.

Write and optimize complex SQL to analyze automotive marketing and inventory data; audit and standardize large datasets; investigate CRM/data discrepancies; build and maintain client-facing BI dashboards and reports; perform QA on datasets and reports; collaborate with US reporting team and fulfill ad-hoc data requests.

Lead architecture, operation, and continuous improvement of cloud-native, enterprise-scale data platforms (Snowflake, cloud storage, streaming). Translate requirements into roadmaps, design and optimize data warehouses and lakes, automate operations with Python and IaC, mentor engineers, and deliver managed services across multiple client accounts while driving reliability, security, and performance.

Lead design, implementation, and optimization of cloud-native data platforms (Snowflake, AWS, Azure) for managed-services clients. Translate business requirements into secure, scalable architectures, drive migrations and performance tuning, and provide hands-on technical leadership. Collaborate with cross-functional teams, mentor junior engineers, and contribute to best-practice frameworks, automation, and pre-sales efforts.

Lead operation, reliability, and continuous improvement of cloud data platforms (streaming, lakes, warehouses). Provide architecture and hands-on operational support, collaborate cross-functionally, drive automation, mentor engineers, and act as trusted advisor for enterprise clients.

Perform quantitative and qualitative analyses to support business planning, forecasting, and operational reporting. Design reports and dashboards, analyze trends and data quality, support modeling and databases, and provide recommendations to business units. Coordinate cross-functional reporting, document requirements, and present findings to management.