Top Entry Level Data & Analytics Jobs in San Francisco Bay Area, CA

As an Analyst, you will conduct analyses for Hive's offerings, support project delivery, collaborate with teams, and communicate project outcomes.

Maintains and verifies client and matter data across business intake and conflicts systems. Processes engagement, waiver, closure, and name-change requests; links parties; maintains ethical walls, database alerts, and administrative files; performs data cleanup and reporting projects; supports technology testing; and communicates intake and risk-management procedures to attorneys, staff, and external parties.

TigerGraph seeks individuals to promote their scalable graph database technology used for analytics and machine learning across various industries.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

Cellanome is looking for passionate individuals to join their start-up team aimed at tackling significant challenges in biology. They offer diverse roles, emphasizing collaboration, innovative spirit, and career growth opportunities.

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

Develop ETL and data visualization solutions for a big data customer and partner experience transformation program. Build native Hadoop and Vertica ETL pipelines, collaborate with stakeholders, and support data integration and visualization deliverables for analytics teams.

Datastage Developer role in banking. Responsible for developing, maintaining, and troubleshooting DataStage ETL jobs to support data integration and reporting. Collaborate with stakeholders and teammates to ensure reliable data delivery and performance.

DiffUSE seeks individuals interested in interdisciplinary roles involving computational biology, machine learning, and open scientific tooling. Responsibilities include data processing, ML research, infrastructure engineering, and community building.

This position involves supporting client-based data analytics and engineering projects, utilizing SQL, Python, or R, and presenting findings clearly.