Top Remote Data Engineer Jobs in Los Angeles, CA

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

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.

The Data Engineer will manage data extraction pipelines, modernize data systems, implement monitoring tools, optimize workflows, and support compliance requirements using various tools and platforms.

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

Lead design, development, and maintenance of scalable, secure data architecture and ETL pipelines. Mentor engineers, optimize data storage and processing, modernize legacy systems, enforce data quality and governance, and collaborate cross-functionally to align data solutions with business strategy.

Implement client revenue cycle data into company systems by creating and configuring ETL processes, building data transformations and logical/physical schemas, documenting solutions in Jira, attending client meetings, and mentoring team members to ensure post-implementation data integrity.

Design, build, and maintain scalable ETL/ELT pipelines and Power BI dashboards; write testable Python, R, and SQL code; enforce version control and engineering standards; partner with data scientists to productionize analytics; explore AI tools; and mentor junior staff.

Lead end-to-end enterprise data migrations and consolidations from legacy ERPs to cloud platforms. Design cloud architecture, build automated ETL/ELT pipelines and ontology-driven schemas, implement CDC and validation frameworks, deliver dashboards and migration controls, advise executives, and develop reusable accelerators while mentoring teams and enabling client post-migration governance.

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.

Design and deploy scalable data infrastructure and models, maintain CDC pipelines, build reporting tools and dashboards, write high-performance SQL, partner with product and engineering to enable enterprise-wide analytics and data-driven decision making.

The Data & Analytics Engineer will model and serve data, improve architecture, and collaborate with teams to sustain the data strategy, requiring 5+ years of experience.

The Senior Data Engineer will manage and transform data pipelines, implement changes in Snowflake, monitor costs, and resolve data issues.

The Senior Quantitative Data Engineer will build and maintain scalable data pipelines for quantitative investment research, ensuring data integrity and compliance, while collaborating with various teams for data architecture and product strategy.

Nagarro seeks an Associate Principal Engineer in Big Data to leverage extensive IT experience for strategic organizational value. The role values self-starters and innovation.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

Design, build, and operate scalable batch and streaming data pipelines; partner with customer and product teams to implement health system integrations; improve monitoring, tooling, and data accessibility; serve as a dataset and tooling subject matter expert.

Technical leader building scalable data pipelines, analytics infrastructure, and APIs. Own architecture, optimize large-scale query performance, mentor engineers, and partner with product and integration teams to deliver real-time and historical analytics.

Design, build, and maintain secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS, and operational workloads. Lead ingestion/transformation pipelines, implement distributed/event-driven processing (Spark/Kafka), enforce governance, observability, and SLAs, and mentor engineers while partnering with data scientists and stakeholders.

Design, build, and operate cloud-native data platforms and scalable pipelines using Snowflake and dbt. Lead orchestration, CI/CD, observability, and performance tuning. Collaborate on backend services and limited frontend work, mentor engineers, define modeling standards, and participate in multi-team architecture and system design.

As a Senior Data Engineer, you'll design, build, and optimize data infrastructure while collaborating with teams to enhance data flow and integration across platforms.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Design and maintain high-quality data pipelines, develop DBT models, collaborate with analytics and data science teams, and optimize data operations for scalability.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

The Senior Data Engineer is responsible for building scalable data solutions, collaborating with teams, and mentoring while overseeing data governance and strategy execution.

As a Senior Data Engineer, you will enhance the data lakehouse, optimize data workloads, perform complex transformations, and develop frameworks to improve delivery velocity, focusing on cybersecurity solutions.