Top Data Engineer Jobs in Los Angeles, CA

The BI Data Engineer will build data pipelines, develop data models, conduct analyses, and drive BI tool usage across teams.

As a Data Engineer, you'll design and maintain data platforms, develop data pipelines, collaborate with teams, and ensure data quality for diverse stakeholders.

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

The Lead Data Engineer will develop data infrastructure, manage event structures, design storage architecture, and mentor engineers for better data practices.

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.

The Staff Data Engineer will architect and operate the Databricks lakehouse, managing data ingestion, governance, and analytics collaboration with cross-functional teams.

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

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

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.

Design, build, and maintain scalable data infrastructure in the cloud using AWS services and Infrastructure as Code to ensure data reliability and performance.

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 Sr. People Analytics Engineer will lead HR data governance, build data pipelines in Snowflake, and create Power BI dashboards, enhancing HR analytics capabilities.

The Sr. Data Engineer will build and optimize data pipelines, support data strategies, and leverage AI tools, with a focus on software engineering best practices.

The role involves developing AI applications, building data pipelines, maintaining analytics infrastructure, and collaborating with sales teams to enhance go-to-market strategies using data-driven insights.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

The Senior Data Engineer will focus on ingesting and curating satellite imagery and geospatial data, building data pipelines, and mentoring junior engineers, while ensuring performance and scalability.

The Senior Data Analytics Engineer designs and implements data models and analytics solutions, oversees data pipelines, and collaborates with teams to drive insights.

As a Staff Data Engineer, you will enhance and modernize data platform infrastructure, manage data processing platforms, and mentor junior engineers.

In this role, you will design and maintain ETL processes, collaborate with teams for data insights, and utilize various programming tools to enhance operations.

The Jr ETL Data Integration Developer will assist in building data pipelines, support data extraction and transformation, and collaborate with teams to understand data requirements.