Top Remote Senior Data Analyst Jobs

Analyze and transform cloud data using SQL, dbt, and Google Cloud; build automated pipelines, data visualizations, validation checks, unit tests, monitoring, and alerts. Partner with engineering teams and enterprise insurance clients to improve data quality, governance, automation, and decision-making. Communicate insights clearly, document technical work, develop insurance domain expertise, and contribute to collaborative reviews and on-call support.

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.

Administer and improve Workday and multi-platform HR security, including role-based access, security groups, access reviews, request approvals, audit support, governance documentation, and compliance controls. Evaluate elevated access requests, identify risks, resolve routine issues, coordinate remediation, and escalate complex decisions. Partner with HR, IT, Legal, and Compliance stakeholders to strengthen policies, processes, and least-privilege access across Workday, Peakon, UKG, Prism, and HR data platforms.

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.

Develop and govern financial data solutions for Liberty Mutual’s Finance Data Platform. Analyze source data, define transformation and downstream reporting requirements, apply metadata, lineage, security, and compliance principles, and build proof-of-concept solutions using coding and financial data expertise. Collaborate with business and technology stakeholders, define impactful metrics, enable self-service data consumption, mentor junior associates, prioritize Agile work, and identify Gen AI applications for data discovery and documentation.

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.

Analyze platform, product, customer, advertising, and operational data to generate actionable insights. Build dashboards, reporting frameworks, automated workflows, and scalable analytics pipelines. Evaluate experiments and analytical methodologies, improve forecasting and data accuracy, and partner with product, engineering, marketing, revenue, and leadership teams to influence strategy, customer experience, and platform growth.

Own the end-to-end data request pipeline, conducting analyses, creating reports and dashboards, investigating data quality issues, and communicating actionable insights to internal and external stakeholders. The role develops analytical scripts, supports machine learning and forecasting models, maintains data governance, integrates third-party data, and improves reporting workflows. It requires expertise in animal sheltering data, strong organization, statistical analysis, visualization, and collaboration across technical and non-technical audiences.

Leads enterprise business intelligence and analytics solutions using Power BI and Microsoft Fabric. Designs semantic models, certified datasets, dashboards, DAX calculations, data transformations, security controls, and governed self-service analytics. Assesses and modernizes reporting portfolios, develops predictive and forecasting capabilities, gathers requirements, validates data quality, supports documentation and adoption, and mentors analysts. Collaborates with business, engineering, governance, and security stakeholders to establish scalable enterprise analytics standards.

Owns analytics for a healthcare claims reprocessing and payment integrity team. Builds operational dashboards, reports, and repeatable SQL data pulls; analyzes cycle time, recovery volume, queue health, and workload; validates data quality; documents metric logic; and partners with operations, IT, and data teams in a regulated environment. Requires advanced SQL, Power BI, Python, healthcare claims experience, and familiarity with payer systems such as QNXT or Facets.

Analyzes healthcare claims, clinical, administrative, and real-world data to develop and validate quality measures and certification criteria. Builds analytical datasets and pipelines using cloud platforms, performs data quality validation, and supports interoperability initiatives. Translates complex findings into recommendations, dashboards, presentations, and executive insights while partnering with clinical, product, business, and technology teams. Contributes to predictive analytics, risk stratification, benchmarking, and evidence-based healthcare quality improvement.

Develops and governs financial data solutions for Liberty Mutual’s Finance Data Platform. Responsibilities include analyzing source data, defining transformation and downstream reporting requirements, applying metadata and lineage principles, prototyping coded solutions, testing, enabling self-service data consumption, defining business metrics, mentoring junior staff, and collaborating across finance, business, and technology teams. The role also identifies opportunities to use generative AI for data discovery, documentation, lineage summarization, prompt engineering, and code generation.

Own and evolve Looker as the company-wide business intelligence platform. Build dashboards, data models, pipelines, and integrations connecting Snowflake and other sources. Ensure data quality and provenance, support operational reporting, and partner with Finance, Data Science, and business teams. Help develop AI- and LLM-based agentic reporting tools that enable self-service analytics. Communicate technical concepts across the organization and provide insights for operational decision-making.

Design and administer enterprise dashboards and reporting solutions (Tableau, Power BI, Microsoft Fabric). Translate complex business questions into compelling data stories, partner with stakeholders and BI engineers, champion visualization standards and governance, mentor analysts, and improve reporting usability and trust across the organization.

Own high-impact data products, ingestion pipelines, and granular data feeds end to end. Analyze massive datasets to answer client and stakeholder questions, ensure data accuracy, and derive actionable insights. Improve products and pipelines by developing methodologies, scaling third-party datasets, and creating data modules. The role requires clear communication, attention to detail, methodical problem solving, prioritization, experimentation, and strong ownership. Training includes SQL, PySpark, Python fundamentals, and internal tools.

The role involves improving transaction monitoring rules, analyzing risk patterns, and building dashboards for compliance while collaborating with investigations and compliance leadership.

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.

Analyze complex financial and business data to guide planning, forecasting, investment decisions, and strategic growth. Partner with FP&A, Accounting, RevOps, Product, Marketing, Data Engineering, and analytics teams; automate recurring workflows; build self-service dashboards and data assets; improve analytics infrastructure; and communicate actionable insights to technical and non-technical stakeholders.

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.

Leads analysis, mining, modeling, and visualization of large-scale transactional, operational, and customer data. Partners with compliance teams to prioritize analytical use cases, support regulatory requirements, improve business efficiency, and translate complex findings into actionable recommendations. Oversees multidisciplinary analysts, manages stakeholder data requests, assesses business changes, and develops analytical systems using machine learning, big data technologies, and visualization tools.

Supports a Department of Defense project assessing service members’ fitness for duty and eligibility for disability separation or retirement. Analyzes systems and business data, identifies data frameworks, supervises personnel, and integrates system-level data requirements and architectures into enterprise architectures compliant with DoD regulations.

Own finance, accounting, and revenue operations data pipelines; develop revenue forecasts; conduct analysis; and build scalable SQL solutions, dashboards, and reports. Partner with executives and cross-functional stakeholders to translate complex financial data into accurate insights and recommendations. Maintain rigorous data validation, documentation, QA, and process improvements while managing competing priorities.

Develop and maintain data models, semantic layers, dashboards, and Python- and SQL-based reports for claims analytics. Analyze operational performance, investigate root causes, and provide actionable recommendations to leadership. Collaborate with engineering, operations, and other stakeholders to translate source systems into standardized data models and deliver effective analytical solutions. Communicate findings through clear writing and presentations while helping shape a growing data team.