Top Data Engineer Jobs in Los Angeles, CA

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.

As a Data Engineer, you will design and implement data platform capabilities, support compliance, and ensure secure data consumption while mentoring clients and improving data pipelines.

As a Senior Data Engineer, you will lead data infrastructure projects, manage ETL pipelines, collaborate with analysts, and improve data models and processes.

As a Senior Data Platform Engineer, you will develop tools for data quality checks, enhance data lineage framework, and improve data infrastructure performance.

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

The Data Engineer II will design and optimize scalable data pipelines for machine learning and analytics, collaborating on data-driven solutions with various teams.

The Data Engineer I will build robust data models, maintain data infrastructure, ensure data quality, and collaborate with analysts and scientists for business insights.

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

The Epic Cogito Data Engineer will gather reporting requirements, design and develop reports, and provide post-implementation support in healthcare IT.

Design and maintain data pipelines, manage Hightouch syncs, optimize SQL queries, troubleshoot issues, and collaborate with stakeholders. Requires 5+ years in data engineering.

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.

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

As a Data Engineer, you will design and build scalable data pipelines, monitor data quality, support data governance, and enhance operational performance for Wikimedia's data ecosystem.

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.

The role involves designing, developing, and maintaining ETL pipelines, ensuring data integrity from various sources, and collaborating with data engineers and stakeholders to fulfill business requirements.

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

The Data Engineer will work on data migration and transformation in an Azure environment, developing designs, securing data transfers, and conducting data profiling.

The role involves building and optimizing data pipelines, managing data integration, supporting analytics, and collaborating with cross-functional teams to enable data-driven decisions.

Design and build data pipelines, develop and maintain scalable data infrastructure, collaborate across teams, and implement data quality frameworks.

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 Senior Data/ML Engineer will create scalable data/ML systems, maintain data products, and enhance business intelligence solutions through collaboration and ownership.

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

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.