Top Analysis Reporting Jobs in Richmond, VA

Lead development of Marriott's cloud data platform, build and own large-scale ETL pipelines on AWS and Snowflake, mentor engineers, manage service provider deliverables, ensure governance, data quality, deployment and production support, and research emerging AI/ML capabilities.

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.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

Support Data Services by analyzing and validating data using SQL and Excel, perform quality checks and reconciliations, monitor production workflows, communicate status and escalations, and identify process improvements. Act as liaison between business stakeholders and technical teams to ensure accurate, timely data deliverables.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.

As a Senior Analyst, you will develop data-driven solutions in collaboration with operations teams and deliver insights through reports and dashboards to improve patient outcomes.

We are seeking a Data Engineer to design, build and optimize scalable data pipelines. Strong experience in Databricks, PySpark, and data warehouse concepts is required.

Perform full-stack on-chain and product analytics: query on-chain data, profile ecosystem actors, benchmark protocols, define KPIs, build dashboards, and translate findings into actionable briefs for strategy, BD, product, and growth teams.

Own user attribution and acquisition analytics across paid and organic channels. Build Segment and AppsFlyer pipelines into Snowflake, write performant SQL and dbt-style models, reconcile CAC/LTV metrics, and ship Metabase dashboards. Track funnel from first touch to activation, identify drop-offs, run growth experiments, and use AI tools (Claude) to automate reporting and insights for marketing leadership.

Own Splash's growth analytics and attribution stack (AppsFlyer, Segment, Snowflake, dbt). Build attribution and LTV/CAC/payback models, maintain pipelines and reporting, drive funnel and contest analysis, reconcile ad spend to revenue, mentor junior analysts, and partner with marketing, product, and finance to inform budget and growth decisions.

Drive process improvement and automation by identifying inefficiencies, developing automations and data pipelines, analyzing KPIs, and designing LLM/ML-enabled solutions in collaboration with AI. Support analytics, SQL/Databricks work, and deliver data-driven insights to improve operational efficiency.

Drive commercial KPIs across Southeast Asia by analyzing performance metrics, delivering insights to senior leadership, guiding sales teams to opportunities, supporting commercial rollouts and ad-hoc campaigns, and collaborating with stakeholders.