Top Data Analyst Jobs in Seattle, WA

Analyze contributor performance, dataset quality, production efficiency, and client delivery metrics. Build dashboards and reports, conduct cohort and trend analysis, monitor quality benchmarks, identify data integrity issues, and translate findings into actionable recommendations. Collaborate with Data Operations, Engineering, Product, and Quality Assurance teams to define metrics and evaluate improvements.

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.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Creates, analyzes, edits, and maintains GIS data supporting fiber and HFC network planning, design, construction, and regulatory map updates. Uses ArcGIS and ArcFM to manage geodatabases, spatial datasets, parcel data, route assets, and network schematics. Conducts map research, interprets technical records, supports GIS projects, develops mapping standards, and responds to internal requests. Collaborates with legal, market expansion, engineering, construction, and design teams while ensuring geospatial data quality and alignment with GIS best practices.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Analyze clinical data completeness, reliability, and effectiveness across healthcare facilities, vendors, interoperability networks, and integration pathways. Reconcile claims with clinical records, identify missingness and latency, report ADT coverage, evaluate data technologies, recommend vendor configurations, and prioritize facilities for direct acquisition. Partner with product, engineering, and clinical teams to improve scalable, trustworthy data pipelines and support TEFCA and QHIN strategy.

Analyze and tune sanctions, fraud, and AML models; evaluate performance, reduce false positives, develop features and datasets, automate analysis, troubleshoot data issues, and communicate findings to technical, compliance, regulatory, and senior management stakeholders.

Analyze cybersecurity and continuous-diagnostics data to identify vulnerabilities, control gaps, asset issues, and risk trends. Validate and normalize data, reconcile asset and vulnerability records, develop dashboards and reports, and provide remediation recommendations. Coordinate with system owners and security teams to resolve discrepancies and verify remediation. Document analytical methods, data definitions, assumptions, and results.

Analyzes the RFQ-to-award pipeline, consolidates and validates business data, and develops dashboards, scorecards, forecasts, and executive reports. Evaluates win rates, proposal activity, pipeline health, revenue opportunities, and performance trends. Partners with program management, sales, engineering, estimating, and business development teams to improve data quality, standardize KPIs, automate reporting, identify process bottlenecks, and support strategic decisions.

Performs data quality assurance for large datasets by validating imports, updates, transformations, and extracts. Writes SQL test queries, reviews database logic, executes test cases, identifies defects, verifies corrections, and documents testing results. Collaborates with data engineers, business analysts, project managers, and QA professionals to ensure data integrity and compliance with requirements.

Analyzes KPIs, product performance, marketing campaigns, and digital customer behavior. Creates Adobe-based visualizations and workflows, defines metrics aligned with enterprise goals, gathers requirements, develops acceptance criteria, and supports testing and validation. Acts as a liaison among product managers, data engineers, and visualization teams while interpreting analytics for executive reviews. The role requires stakeholder facilitation, strong communication, Adobe Analytics expertise, and on-site work in Seattle.

Senior individual-contributor analyst leading end-to-end, high-stakes analyses, designing dashboards and reporting, mentoring analysts, applying statistical methods and causal inference, partnering with analytics engineering to shape warehouse models, and translating findings for technical and non-technical stakeholders.

Build dashboards and self-service analytics for Microsoft eCommerce, analyze customer funnels and performance drivers, investigate revenue and product trends, support experimentation, validate data quality, establish KPI standards, and communicate actionable insights to technical and business stakeholders. Use SQL, Python, Power BI, Adobe Analytics, and AI-assisted tools to improve reporting and decision-making across web, marketing, and commerce teams.

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.

Collects and analyzes performance data, identifies trends, evaluates program effectiveness, and develops reports and visualizations for stakeholders. The role standardizes datasets, improves data collection and analytical methods, and supports data-driven decisions. It requires statistical analysis, data manipulation, visualization, and familiarity with machine learning and predictive analytics. The position is contingent on contract award and requires the ability to obtain and maintain an active Secret Clearance.

Analyzes complex sustainability datasets, validates calculations and metrics through QA and UAT, maintains assessment files and customer data exports, investigates data issues using SQL, and collaborates with product, engineering, and customer-facing teams. The role also supports automation, documentation, sustainability research, and reliable environmental impact reporting.

Own and maintain the data catalog, vendor and licensing records, dataset lineage, field definitions, and calculation documentation. Write SQL to trace, join, reconcile, and validate data; investigate discrepancies; QA derived metrics; prepare data extracts; and troubleshoot issues with engineering, offshore data teams, PMO, and customer service. Use AI tools to accelerate data work and maintain clear documentation for technical and non-technical stakeholders.

Leads stop loss claims data coordination for primary clients, identifies claimants, prepares claim-entry data, builds dashboards, presents insights to leadership, and drives continuous improvement initiatives. Requires at least three years of claims data analysis or operations experience, specific stop loss claims expertise, and a bachelor’s degree in Business or Analytics or comparable experience.

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.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Senior Data Analyst responsible for integrating sales, CRM, customer, campaign, product usage, and engagement data into forecasts, dashboards, recurring reports, datasets, and actionable insights. The role analyzes pipeline performance, customer health, product adoption, retention, churn, marketing campaigns, and commercial trends. It partners with cross-functional stakeholders, defines KPIs, improves data quality, prepares executive reporting, and supports strategic decision-making through clear analysis and recommendations.

Own end-to-end financial data analysis, including SQL and dbt data modeling, Looker dashboard development, data quality validation, reconciliation, and stakeholder-facing insights. Partner with Finance and Payments to support reporting, planning, revenue analysis, cost insights, and transaction-level analytics. Translate ambiguous business needs into reliable technical solutions while improving documentation, QA, modeling, and data architecture practices.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Drive client growth for Circana’s Foodservice team by selling data and software solutions, managing end-to-end sales cycles, translating POS and consumer data into actionable insights, building stakeholder relationships, meeting revenue targets, and collaborating with analytics, product, and client insights teams.