Top Remote Senior Data Analyst Jobs

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Senior Data Analyst delivering complex reporting, analytics, and insights for Medicare Advantage supplemental benefits. Build and maintain ETL/ELT pipelines, scalable reports, dashboards, and data products using SQL, Snowflake, Databricks, and Python/PowerShell. Partner with stakeholders and vendors to ensure data quality, compliance, and actionable recommendations; mentor colleagues and drive process improvements.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Design and execute clinical evidence studies by developing dbt/SQL data models, automation pipelines, and reports. Integrate and de-identify clinical data across marts, build analysis-ready datasets, maintain code quality, validate outputs, and create visualizations and KPIs to support oncology-focused research and clinical decision-making.

Lead ownership of client billing data and infrastructure for Finance: run reconciliations, investigate billing issues, build BI dashboards, automate workflows with SQL/Snowflake, monitor revenue leakage, and support Billing 2.0 UAT while training Finance on reporting and Looker standards.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Analyzes complex federal healthcare datasets to identify trends, risks, and opportunities; develops models, dashboards, reports, and visualizations; presents recommendations to leadership; supports project tracking, status reporting, risk and cost monitoring; ensures data quality across systems; and collaborates with technical and business stakeholders using VHA data sources.

Develop and support analytics deliverables, including sales, marketing, customer, and performance analyses. Query and transform large datasets, automate data processes, build dashboards and visualizations, and deliver actionable insights through reporting and presentations. Partner with clients and internal stakeholders to define analytical needs, evaluate campaign effectiveness, analyze customer behavior, and support strategic decisions.

Own end-to-end analytics across marketing, revenue, product, and partnerships. Build reliable data models and semantic layers in a lakehouse, maintain dashboards and monitoring, investigate anomalies, conduct experimentation, and translate complex analyses into recommendations for senior stakeholders. The role requires advanced SQL, Python, data modeling, stakeholder communication, autonomy, and mentoring, with responsibility for improving data quality and building analytical standards in a high-growth startup.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Design and deliver AI-powered analytics, dashboards, and decision-support tools for commercial healthcare teams. Build LLM-based agents, use cloud data platforms (Azure/AWS/Snowflake), ensure data governance and compliance, translate complex healthcare data into executive-ready insights, and automate insight generation to support growth and operations.

Analyze complex datasets to generate actionable insights, primarily using Power BI and advanced SQL. Create documentation, blogs, and tutorials; mentor junior analysts; and work directly with customers to understand requirements and resolve data analysis issues. The role also involves Azure data analytics services, advanced Excel, and preferably ETL, data warehousing, data modeling, Power Automate, and Power Apps.

Lead healthcare payment integrity analyses, collaborate with clients and internal teams, build and maintain large-scale SQL and Spark queries, design ETL/ELT transformations, implement AI/LLM-driven analytical workflows, perform data quality monitoring, and mentor analysts while documenting lineage and audit-ready methodologies.

Analyze claims data using Python, SQL, dbt, PostgreSQL, Looker, and Excel; build ETLs, data models, reports, and visualizations; lead customer calls; provide technical recommendations; clarify requirements; and communicate precise insights while collaborating with engineering and operations teams.

Lead retention and marketing analytics: build lifecycle and segmentation frameworks, design and analyze A/B tests, drive personalization and KPI dashboards, automate retention reporting, and partner with Marketing, CRM, Product, and Data Engineering to turn insights into action.

Lead product analytics across multiple products: own event tracking, funnel analysis, A/B testing framework, AI/LLM-driven insights, dashboards, and reporting. Ensure data quality, define KPIs, run experiments, automate monitoring, and collaborate with Product, Engineering, Marketing, and leadership to drive data-driven decisions.

As a Senior Data Analyst, you'll provide actionable insights by analyzing product and engineering data, partnering with leadership on metrics frameworks and decision support for product delivery.

Design, build, and maintain data pipelines, dashboards, and predictive models. Analyze large datasets to generate actionable insights, collaborate with stakeholders, ensure data quality and governance, and document/share analytics best practices to support Marketing, Product, Operations, and Workforce teams.

Support pharmaceutical brand and commercial teams by transforming and integrating healthcare and media data using SQL and cloud warehouses, performing EDA and statistical analysis, preparing datasets for advanced analytics and ML, and building visualizations and dashboards. Communicate insights to cross-functional stakeholders, document methodologies, and maintain analytical workflows and data governance for marketing and analytics use cases.

Build and maintain scalable monitoring solutions and dashboards to track production, campaign, and operational data. Analyze large-scale datasets to detect anomalies, perform root-cause investigations with Engineering and Production Operations, and deliver actionable insights to improve platform reliability and operational efficiency.

Drive Data Governance requirements, analyze and validate data, collaborate with stakeholders, and maintain Data Governance artifacts using SQL and Informatica tools.

Build and maintain SQL queries and automated data workflows to support CARF and 1099-DA regulatory reporting. Validate, reconcile, and document reporting data; partner with cross-functional teams; track work in Jira; identify automation opportunities; support testing, audits, and jurisdictional implementations.

Analyze C&DS project data to produce actionable insights. Build data pipelines, reports, visualizations and predictive/prescriptive models. Collaborate with IT, data governance, and business stakeholders to enable data-driven decision-making, support reporting needs, and ensure data quality and access.

Lead cross-functional analyses and build scalable reporting for go-to-market teams. Develop and automate data pipelines, create interactive dashboards, improve data quality, and translate complex findings into actionable recommendations for stakeholders and executives.