Top Remote Data & Analytics Jobs in San Diego, CA

Designs and supports enterprise data integrations, ETL/ELT pipelines, APIs, data models, and transformations across Microsoft platforms. Maintains data quality, governance, security, and reliability while developing CI/CD pipelines, deployment automation, and release processes. Troubleshoots integration and deployment issues, manages environments, supports reporting and analytics, and collaborates with technical and business stakeholders to deliver scalable data solutions.

Develop and optimize enterprise Oracle SQL and PL/SQL solutions, including data models, database designs, APIs, ETL processes, batch jobs, and performance tuning. Collaborate with cross-functional teams to translate requirements into scalable implementations, support testing and CI/CD, troubleshoot production issues, and document solutions. Provide technical leadership, mentor engineers, participate in architecture and code reviews, and drive engineering best practices across data modernization initiatives.

Own board-grade analytics deliverables for client engagements by transforming Salesforce pipeline data and BI outputs into executive narratives, presentations, and reusable reporting templates. Analyze pipeline, funnel, and revenue performance; explain variance; write causal commentary; present findings to PE sponsors and executives; and train client teams to maintain deliverables independently.

Own enterprise data governance, metadata, lineage, data quality, master data, GxP readiness, cloud data-layer standards, commercial data controls, partner data exchanges, and AI data governance. Lead federated stewardship, executive scorecards, architecture reviews, access models, vendor data governance, and regulatory readiness across clinical, commercial, and corporate data. Partner with Security, Legal, Privacy, Compliance, and QA while building accountable business ownership and trustworthy, rapidly accessible data.

Build and maintain modern data-centric applications, pipelines, transformations, enrichment processes, provisioning layers, and user interfaces supporting clinical and operational healthcare processes. Analyze clinical data and report trends using cloud, big data, data science, and modern software development practices. Collaborate with Product, Platform, and Architecture teams, mentor Data Engineers, document solutions, manage source control, and research emerging technologies.

Build and maintain full-stack data engineering solutions supporting BioIntelliSense’s remote patient monitoring and clinical intelligence platform. The role likely involves processing health-monitoring data, enabling analytics, and supporting reporting for clinicians, patients, and employers. Specific responsibilities and qualifications are not provided in the description.

Serves as the technical and client-facing link between Inca Digital’s data engine and high-stakes financial and government clients. Conducts OSINT, web scraping, enhanced due diligence, blockchain and crypto investigations; analyzes large datasets; audits and synthesizes technical findings into intelligence reports; briefs executive stakeholders; and coordinates cross-functional teams to align products with client needs.

Leads the data organization across data engineering, analytics, reporting, and data science. Defines data strategy, architecture, governance, quality, and platform roadmaps; manages and develops technical teams; partners with business and engineering leaders; and guides scalable AWS-based data infrastructure, batch and real-time pipelines, and data products that support strategic growth.

Develops and maintains dashboards, reports, data tools, and data infrastructure for Consulting. Analyzes client, project, portfolio, capacity, compliance, and outcomes data to identify trends and support decisions. Maintains data integrity across Salesforce, Resource Hero, Power BI, and related systems; establishes governance standards; trains staff; and manages consulting projects, workflows, budgets, timelines, and deliverables.

Design and deliver modern data platforms, scalable and secure ingestion and transformation pipelines, durable data models, streaming systems, and reporting layers. Partner directly with clients and business stakeholders to translate requirements into architecture, explain tradeoffs, and own delivery outcomes. The role includes production implementation across cloud data platforms, orchestration, governance, real-time technologies, and analytics or AI data consumption.