Top Hybrid Data Engineer Jobs in San Diego, CA
Build, orchestrate, and monitor model pipelines, scaling machine learning algorithms, build and enhance ML Engineering platforms, implement ML Ops, write production-ready code, collaborate with client teams, participate in scrum calls, and research latest architecture patterns/technologies.
Director position in the Products & Technology Risk and Quality team at PwC, responsible for managing technology and data risks, regulatory compliance, and stakeholder relationships. Requires strong communication, critical thinking, and decision-making skills.
Join GRAIL as a Staff Data Engineer to support the data needs of clinical and research activities. Automate and enhance data infrastructure to contribute to early cancer detection efforts. Work collaboratively to design, deploy, and automate secure and efficient data infrastructure and tools.
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The Enterprise Data Engineer will provide technical leadership in architecting and delivering end-to-end solutions. They will work with business partners, collaborate with other teams, and develop architecture and design patterns for processing and storing high volume data sets. The ideal candidate should have at least four years of relevant experience, knowledge of data warehouse architectures, and experience with cloud environments, SQL, and real-time streaming data pipelines.
Responsible for defining and driving data governance within the Finance organization. Partnering with leaders and process owners to implement data policies and standards, ensuring data quality and consistency across financial applications.
As a Senior Data Engineer, you will contribute to Tendo's strategic data engineering solutions by ingesting, transforming, and warehousing healthcare-related data from various sources. You will collaborate with Data Scientists and Product Managers to produce quality data flows and transformations, and develop tools and solutions for data integration and modeling. The ideal candidate should have a strong background in software engineering, data modeling, and data warehousing.
Senior Analytics Engineer responsible for data discovery, data modeling, data engineering, and data governance using Databricks, dbt, and Python. Develops data pipelines, implements data quality checks, and optimizes data pipelines for performance. Creates data visualizations and communicates insights to stakeholders. Requires 5+ years of Data Engineering experience and expertise in Python, Databricks, SQL, and AWS.
Top hybrid Companies in San Diego, CA Hiring Data + Analytics Roles
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