Top Remote Analysis Reporting Jobs in San Diego, CA

Support JDA/Blue Yonder WMS, configure systems for customer implementations, test new code, and collaborate with teams for operational improvements.

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.

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.

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.

The IT Senior Analyst will gather requirements, lead testing, manage integration projects, and mentor team members in a high-paced environment.

Design, optimize, and govern Komodo's Snowflake-centered data infrastructure, integrate with Databricks and adjacent stores, reduce costs and improve query performance, implement monitoring/automation, establish metadata and RBAC governance, and coach teams on best practices to meet compliance and performance SLAs.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.