Top Data Engineer Jobs in Los Angeles, CA

As a Data Engineer at Circle, you'll manage data pipelines for blockchain analytics, ensuring data accuracy and quality to support business functions. Responsibilities include building ELT pipelines, designing data models, and improving warehouse operations.

As a Data Engineer, you'll manage data warehousing and pipelines for blockchain analytics, ensuring data accuracy and supporting business functions. You'll collaborate with teams to improve operations and leverage AI for efficiency.

As a Data Engineer, you will manage the data warehouse and ELT pipelines for blockchain analytics, ensuring data accuracy and quality for product development and business growth.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

The Data Engineer will enhance the enterprise Data Lake by integrating data sources, ensuring data accessibility, and supporting analytical teams through data ingestion, transformation, and governance in both cloud and on-prem environments.

Lead the evolution of SimplePractice's data stack, building scalable systems for analytics, reporting, and product insights in a fast-paced environment.

The Senior Data Engineer will develop and maintain data pipelines, collaborate with Analysts, and ensure high code and data quality on the Hungryroot Analytics model.

Lead design and delivery of data solutions in Adobe Experience Platform, optimize data models, mentor junior engineers, and drive strategy.

The Freelance Data Engineer will analyze data, design databases, manage data operations, and collaborate on data-driven projects to optimize data infrastructure.

The role involves acquiring and analyzing new data sources, building pipelines, and collaborating to support quantitative research and trading strategies.

Seeking an experienced Data Engineer to design and optimize data infrastructure, build scalable pipelines, and ensure data quality and governance.

As a Staff Data Engineer, you'll architect and model data, create ETL pipelines, and standardize datasets for compliance teams. You'll guide best practices and lead data solutions while collaborating with various stakeholders.

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

Design and optimize data pipelines, work with structured/unstructured data, ensure data quality for analytics, and collaborate with data scientists.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

As a Data Warehouse Engineer, you'll build reusable internal data products, design scalable pipelines, and collaborate with stakeholders for actionable insights.

As a Data Engineer, you'll manage data access, support development and analytics teams, implement automated processes, engineer data pipelines, and ensure data accuracy.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

Lead the implementation of AML detection pipelines using Palantir Foundry. Train team members in technical skills and oversee data architecture and maintenance.

Design and build scalable platforms for data ingestion and storage, collaborate with hardware engineers, and define engineering processes at Sift.

As a Data Engineer, you will build and optimize data pipelines, manage ETL workflows, and ensure efficient data access and quality within the infrastructure.

Design and deploy data processing pipelines, analyze data to extract insights, and develop software systems for data management and privacy.

The Data Engineer will build ETL pipelines and data infrastructure, ensure data quality, and implement modern data warehousing for analytics improvements, while collaborating with stakeholders across teams.

The Data Architect designs data flows, defines standards, ensures data quality, and collaborates on data strategies while integrating advanced technologies.