Top Analysis Reporting Jobs in Santa Cruz, CA

The ETL Developer will design, develop, and test ETL scripts using the Informatica platform, gather requirements, and maintain database applications. They will also provide end-user support post-deployment and ensure requirement fulfillment.

The Senior Korean Linguist manages translation and copy-editing tasks, coordinates with freelancers, and ensures high-quality Korean-language deliverables while improving workflows and supporting quality efforts.

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.

Design and maintain data systems for business-critical insights, connect data across platforms, build ETLs, and support business data decisions.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

The IBM TM1 Developer will manage the SDLC for Finance applications, focusing on TM1 and migrating from Essbase, while collaborating with global teams.

The Data Engineer builds and maintains data infrastructure, develops data pipelines, ensures data quality, and collaborates with teams for insights.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

The Principal Data Architect will design and evolve enterprise data architecture to support business growth and AI integration, ensuring a secure and efficient data ecosystem while collaborating with various teams to enhance data quality and governance.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.