Top Data & Analytics Jobs

Leads commercial analytics and business intelligence for global eCommerce by extracting enterprise data, identifying trends and performance drivers, and creating executive-ready Power BI dashboards, reporting views, and insight narratives. Defines KPI architecture and measurement logic, supports data-quality and reporting standards, and collaborates with data, BI, engineering, and commercial analytics teams to deliver trusted, actionable insights.

Analyze NPS, customer experience metrics, survey data, and multiple data sources to identify trends and drivers. Build and maintain dashboards and recurring reports, synthesize findings, and translate analysis into clear narratives and actionable recommendations. Partner with CX, research, analytics, and business stakeholders to answer complex questions, support measurement initiatives, and inform customer experience strategy.

Support Business Intelligence and Business Development teams through SQL data analysis, Tableau dashboard development, reporting automation, process documentation, and pipeline visibility. The intern will work with relational databases and tools including Snowflake, SSRS, Python, and Tableau while supporting cross-functional reporting requests. The role includes mentorship, knowledge-sharing, and presenting findings at the end of the summer program.

Analyze logistics data to evaluate shipping performance, rates, surcharges, and service standards. Develop data models, forecasts, visualizations, executive summaries, and presentations that support strategic decisions and improve logistics operations. Collaborate cross-functionally to deliver actionable business insights using predictive analytics and AI-enabled tools.

Administers and protects product-related ERP data, validating records, maintaining documentation, updating costs, performing cost roll-ups, reviewing manufacturing orders, and supporting accurate data processes across departments.

Supports incrementality testing and marketing mix modeling for ecommerce clients. Responsibilities include validating datasets, assisting with experiment design, analyzing results, diagnosing model and data issues, investigating client trust queries in SQL, contributing to forecasting and budget scenarios, and explaining methodology to clients. The role also involves documentation, incident logging, and fact-checking marketing claims under close supervision.

Provides technical leadership and supervision for enterprise data operations, including ETL/ELT pipelines, ingestion, scheduling, monitoring, recovery, data quality, and platform support. Designs secure, scalable architectures; oversees NIST-aligned controls, access, encryption, audit logging, and data governance. Coordinates incident management across technical teams, establishes operational KPIs, leads modernization and automation, and mentors data engineers, ETL specialists, analysts, and support staff.

Designs and implements scalable software solutions, develops maintainable features, resolves bugs, optimizes performance, and writes automated tests. Participates in architecture discussions, code reviews, Agile planning, CI/CD, observability, and adoption of AI-assisted engineering tools. Collaborates with QA, Product Management, and DevOps to deliver software across web, desktop, cloud, and IoT environments. The role is remote for candidates in the Seattle or Los Angeles metropolitan areas, with quarterly travel to Los Angeles.

Contribute data analysis, open-source reporting, visual verification, and investigative journalism to projects involving datasets, satellite imagery, maps, charts, interactive graphics, and digital evidence. Collaborate with reporters and editors, scrape and analyze unstructured data, verify photos and videos, and pitch visual stories while meeting rigorous editorial standards and deadlines.

Designs and evolves enterprise Azure Databricks lakehouse architecture, data models, ingestion and transformation pipelines, governance, security, quality controls, and PostgreSQL stores. Integrates enterprise data sources and develops governed datasets for analytics, AI agents, and RAG workflows. Establishes standards, monitors performance and costs, supports deployment and recovery, and provides technical leadership, design reviews, documentation, and mentorship across technology and business teams.