Top Remote Data & Analytics Jobs in San Diego, CA

Own end-to-end data pipelines for multiple clients: extract, clean, transform, model and visualize data. Build dashboards and automated workflows, apply AI where useful, and present actionable insights to non-technical stakeholders.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Serve as the technical owner for customer-facing data workflows and integrations: build pipelines, write SQL and Python scripts, deploy AI-powered workflows, manage APIs and Snowflake ingestion, and translate repeatable solutions into product requirements while supporting customer success and internal engineering.

As a Memory Developer, you'll record household tasks, shape the robot's memory, and help train its AI for better performance.

The Organic Growth Analyst will support SEO and content strategies for B2B SaaS clients, conduct analyses, and help track performance.

Lead design and development of web UI and REST middleware within an Agile team. Define requirements and acceptance criteria, implement Java/Spring and Angular solutions, build CI/CD pipelines, work with Product Owner and testers, and produce/update design documentation.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The SEO Innovation Specialist will manage SEO strategies, conduct audits, optimize content, and leverage AI tools for performance analysis.

Design, build, and optimize scalable ETL/ELT data pipelines using Databricks and cloud platforms. Implement data quality checks, monitor and troubleshoot jobs, audit pipelines for compliance, and collaborate with analysts and business stakeholders to define data models and support reporting.