Top Data Engineer Jobs in Los Angeles, CA

The Snowflake Data Engineer will design, build, and maintain data pipelines on Snowflake, optimizing performance and ensuring data quality while collaborating with stakeholders.

The Data Engineer builds and maintains data pipelines and platforms, collaborating with Data Scientists and Analysts to optimize data management and integration for insights.

Responsible for designing, developing, testing, and optimizing data integration solutions, focusing on financial month-end closure and ongoing production support.

Thrive Market seeks a Senior Data Engineer to deliver data engineering solutions, collaborate across teams, and manage data architecture, focusing on complex data processing and streaming frameworks.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

The Data Engineer I at Storable supports the design and maintenance of data pipelines, works with ETL processes, optimizes workflows, and collaborates with various teams to enhance data accessibility and reliability.

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

The Data Engineer Consultant will design and implement scalable data solutions, advise clients on optimizing data environments, and develop ETL pipelines and data models to support business objectives.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

As a Databricks Data Engineer, you will design, implement, and optimize Databricks solutions, lead projects, gather requirements, and collaborate closely with clients to ensure successful project delivery.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.

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

The role involves designing and maintaining ETL/ELT pipelines, integrating diverse data sources, automating Fabric environments, and collaborating with global teams on data solutions.

The Data Platform Engineer II role involves automating data infrastructure, scaling analytics platforms, and ensuring system reliability and security. Key responsibilities include managing CI/CD pipelines, configuring secure networking, and collaborating with Data & Analytics teams to optimize performance.

Design, build, and maintain scalable ETL/ELT data pipelines on Databricks and AWS S3; manage large geospatial and temporal datasets; productionize ML models; implement data validation, testing, and monitoring; optimize storage and processing; document workflows; collaborate cross-functionally.

The Staff Data Engineer will develop and optimize data systems, analyze data, and collaborate with teams to deliver scalable solutions in healthcare data management.

The Senior Data Engineer will manage data pipelines, ensure data quality, implement CI/CD processes, and collaborate with analytics teams while enforcing organizational standards.

Design and operate data pipelines for analytics and reporting, ensuring data quality and security, mentoring engineers, and translating data into insights.

The Senior Data Engineer will design, build, and optimize data pipelines using GCP technologies, ensuring data quality and supporting business intelligence needs.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

The Data Engineer role involves designing and maintaining AWS-cloud-native data systems, developing ETL processes, optimizing data pipelines, and ensuring data security and governance in healthcare data applications.

The Principal Data Engineer will lead the design of data frameworks, mentor teams, implement MDM solutions, and ensure data quality across environments.

The Data Engineer Senior will optimize data pipelines, work within scrum teams, mentor others, and improve data quality, reliability, and governance.