Top Senior Data Engineer Jobs in Los Angeles, CA

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The Data Engineer designs and operates data and machine-learning systems for HSA/FSA eligibility, building pipelines, models, and APIs to support decision-making at Flex.

Design and optimize the enterprise data warehouse and ELT pipelines (batch and real‑time). Integrate Databricks, CRM, and external systems into a governed, observable data platform. Drive automation, cost optimization, and monitoring; mentor junior engineers; and partner with Analytics, Ticketing, and Marketing to deliver scalable data solutions that support reporting and ML initiatives.

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.

As a Senior Data Engineer, you'll define data ontology, collaborate with teams, design data pipelines, and optimize data infrastructures to support analytics for Yahoo Mail.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

As a Principal Data Engineer, you will design and implement data infrastructure and solutions, collaborating across teams to enhance healthcare data usage.

Architect and scale cloud data platforms and ETL/ELT pipelines (batch and near-real-time), ensure data quality and observability, implement CI/CD for data infrastructure, collaborate with stakeholders and mentor junior engineers to deliver analytics and machine-learning-ready data products.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

Lead architecture and delivery of Boulevard's data platform, building foundational data models, pipelines, and customer-facing analytics. Collaborate with Product and Engineering to create scalable data products, Snowflake data sharing solutions, performant visualizations, and machine learning features (recommendations, forecasting, anomaly detection) to drive data-driven decision-making and product value.

As a Senior Data Engineer, you will design and optimize data pipelines, enhance system efficiency, and collaborate with teams to drive health outcomes using large healthcare datasets.

The Staff Data Engineer will design data architecture, develop scalable data pipelines, ensure data quality, and lead governance practices while collaborating across teams.

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.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Lead architecture and implementation of scalable data systems and pipelines from ingestion to delivery. Own ambiguous, high-impact integrations, improve data quality and reliability, adopt AI-augmented engineering, mentor engineers, and collaborate with Product, ML, and customer teams to ship production solutions.

Design, build, and maintain scalable batch and streaming data pipelines and analytics-ready data models. Implement cloud (primarily AWS) data platform solutions, data ingestion, transformation, orchestration, and observability. Embed data quality, governance, security, and metadata/lineage practices. Partner with architecture, analytics, and application teams to enable self-service analytics, reporting, and downstream use cases while driving platform evolution and engineering best practices (CI/CD, testing, documentation).

Design, build, and maintain scalable, fault-tolerant streaming data architectures and real-time pipelines using Kafka, MSK, and Kinesis. Implement stream processing, monitoring, security, IaC, and CI/CD. Collaborate with data teams, provide technical leadership, and optimize latency, throughput, and cost for real-time analytics and downstream systems.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

Design and build scalable batch and streaming data pipelines, lead architecture for Lakehouse platforms, and mentor junior engineers while optimizing data quality and performance.

Lead data engineering strategy and design scalable data ecosystems. Build and maintain distributed ETL pipelines, enforce data governance (PII/PHI), improve developer efficiency, mentor engineers, and align technical work to business objectives while delivering reliable, monitored production systems.

Design, build, and scale streaming and batch data pipelines, embedding workflows, and vector store integrations to support AI applications. Implement AI-optimized data models, ensure observability and data quality, and collaborate across infra, ML, and product teams while mentoring engineers and delivering production-ready, reliable data foundations.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

As a Senior Data Engineer, you will manage data pipelines, ensure data quality, partner with teams for data-driven decisions, and improve the data platform while maintaining data integrity.

The Senior Data Engineer will create and manage data pipelines, ensuring data quality, collaborating with teams for data-driven decisions, and evolving the data platform.