Top Data & Analytics Jobs in Santa Cruz, CA

Design, develop, and maintain enterprise data integration (ETL) systems and data platforms. Lead technical designs, optimize performance and scalability, support production issues and off-hours rotations, build reporting and BI solutions, document data processes, and collaborate with stakeholders and vendors to align business requirements.

Design, develop, and optimize ETL/data integration, data platforms, and BI solutions. Lead technical designs, troubleshoot production issues, participate in on-call support, and document processes to ensure scalable, secure, high-performance enterprise data solutions.

The Acquiom Imports Analyst interprets payment data, manipulates spreadsheets for import into NetSuite, and ensures data accuracy for M&A transactions.

The Senior Statistical Programmer will program and validate datasets for clinical trials, oversee deliverables, manage projects, and ensure compliance with industry standards. Requires strong skills in SAS and R for statistical programming.

Build and maintain scalable batch and streaming data pipelines on GCP, develop API-driven integrations, design data models, ensure data quality and performance, and deliver end-to-end solutions in a client-facing healthcare data environment.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.

Run funnel audits and synthesize multiple datasets into exec-ready narratives. Recommend and help launch A/B tests, benchmark against genres and market data, partner with game analysts and ETL engineers to validate and maintain clean data, and provide actionable UA, monetization, and live-ops recommendations to customers.

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 pipelines and Lakehouse solutions; ingest and transform diverse data formats; optimize Databricks and SQL Server environments; implement data quality, lineage, and governance; support batch and streaming ingestion; collaborate with analysts and stakeholders to enable analytics (fraud/anomaly detection, financial oversight); troubleshoot and improve pipelines. Candidates must be willing to undergo a U.S. government background investigation.

Design and implement scalable cloud data platforms and end-to-end ETL/ELT pipelines, migrate legacy infrastructure to Snowflake/AWS, optimize data warehouses, build transformations with dbt and Dagster orchestration, develop data processing with Python and SQL, implement IaC and CI/CD, and ensure data observability and governance while collaborating with stakeholders.