Top Data Engineer Jobs in San Francisco Bay Area, CA

Design, build, and maintain scalable data pipelines and platform tools; define canonical data models; deploy and operate workflow managers (Airflow/Jenkins); work with cloud data tools (Redshift, EMR) and infra (Kubernetes, Terraform); implement data security controls; mentor junior engineers and collaborate with data scientists, analysts, and product teams.

The Staff Data Engineer will design and maintain data systems, streamline workflow for Data Analytics and Machine Learning teams, and ensure data pipelines are efficient and reliable. Responsibilities also include driving large projects, collaborating across teams, mentoring, and supporting the company's strategy.

The Senior Staff Data Engineer at SmithRx will define technical vision, improve data engineering efficiencies, and enhance data governance while mentoring other engineers and leading cross-functional collaborations.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

The Sr. Data Engineer will build and maintain data pipelines, develop ETL processes, and optimize data infrastructure, collaborating across teams to ensure data reliability and performance.

Design and maintain scalable data pipelines, ensuring accurate delivery and governance of data across the organization while collaborating with cross-functional teams.

The Data Engineer will design and maintain scalable data pipelines, integrate APIs, support ML teams, and optimize data systems for performance and reliability.

The Senior Data Engineer will design and maintain data infrastructures, support analytics, and collaborate with stakeholders to improve data quality and governance while utilizing DBT and AWS tools.

The Lead Data Engineer drives enterprise-scale data solutions, oversees project scoping, and leads a team, ensuring best practices in data engineering.

As a Senior Data Engineer, you will implement and optimize Google Analytics systems for accurate user behavior measurement across platforms, ensuring scalability and data accuracy.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

The Senior Data Engineer will design and optimize data infrastructures and pipelines, lead projects, mentor juniors, and enforce best practices.

Design and build Spark ETL pipelines on an AWS data platform, collaborate with stakeholders to deliver reliable large-scale data products, optimize and maintain data infrastructure, ensure data quality/governance, and manage platform operations and incident response.

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

Lead design, build, and optimization of Sezzle's large-scale data warehousing and pipelines. Own data infrastructure KPIs/SLAs, improve Redshift performance, evolve the data stack, implement ETL/ELT workflows, and partner with cross-functional teams to deliver reliable, scalable datasets.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

As a Senior Data & Analytics Engineer, you'll lead data initiatives, manage a team, and ensure data quality while turning insights into actionable decisions across the company.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, focusing on architecture, ingestion, storage, and analytics on GCP. You'll collaborate with stakeholders and optimize data structures for performance while ensuring adherence to data governance and compliance standards.

The Senior Data Engineer will focus on Data Modeling, utilizing SQL, Snowflake, and Apache Airflow to develop efficient data models and deliver data products.

Design, build, and maintain production data pipelines and tooling (CI/CD, testing, validation) using Snowflake, dbt, and orchestration tools. Model, transform, document, and optimize data to produce reliable curated datasets for analytics and solutions, enforce engineering best practices, and mentor teammates while ensuring scalability, observability, and data integrity.

Lead design, build, and support of cloud-based ETL, data warehousing, and reporting solutions. Develop/optimize ETL pipelines, data models, and queries; deploy containerized services on Kubernetes; automate workflows; mentor teammates; collaborate with architects, data scientists, and stakeholders to deliver scalable analytics and reporting products.

Architect, build, and maintain scalable ELT data pipelines and analytics-ready data marts. Lead dbt modeling, ensure data quality, CI/CD, and documentation. Partner with stakeholders, mentor junior engineers, evaluate tooling (reverse ETL), and drive long-term data platform strategy.

Design, build, and maintain production data pipelines and the unified data model using Snowflake, dbt, and orchestration tools. Optimize, test, document, and monitor ELT workflows, enforce engineering best practices, mentor teammates, and deliver trustworthy data products for analytics and business decisions.