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 business and data requirements, assesses data quality and sources, maintains data dictionaries and lineage, defines KPIs, validates reports, and delivers actionable insights. The role supports data governance, PII protection, integrations, data transformation, platform performance, business continuity, and process improvement. It collaborates with stakeholders and data teams, mentors colleagues, resolves complex issues, and contributes to enterprise data strategy and technology decisions.

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.

Conduct forensic analytics for anti-money laundering and financial crime monitoring. Analyze large transactional datasets with SQL and Alteryx, identify suspicious behaviors and emerging typologies, develop and validate detection scenarios, calibrate thresholds, perform lookbacks and segmentation studies, evaluate transaction networks, and support AML investigations, SAR narratives, and regulatory responses.

Work on supply-side product and business analytics for direct accommodation contracts. Build and automate reporting, analyze internal/external data, design prioritization/segmentation and predictive algorithms, and partner with product, commercial, and international teams to improve supplier performance and guide strategic decisions.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

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.

Integrates healthcare billing, payment, and medical review datasets; develops monitoring summaries and analyses; applies statistical sampling, estimation, and hypothesis testing to federal healthcare policy and payment research; and collaborates with analysts and policy experts on projects.

Analyzes healthcare billing, payment, medical review, and claims datasets; develops monitoring summaries; researches federal healthcare policy and payment questions through data querying; and collaborates with analysts and policy experts on project-based work.

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.