Data Engineer Jobs in Berkeley, CA

Design and build data infrastructure, pipelines, and integration solutions using cloud and big-data tools. Develop data lakes/warehouses, ensure data quality and security, apply data modeling and DAGs, use Databricks, Airflow, and Hadoop, and collaborate with clients to deliver actionable insights.

Lead design and implementation of data infrastructure, pipelines, and integrations using cloud platforms. Manage teams and client accounts, ensure data quality, security, and compliance, deploy scalable solutions (Databricks, Snowflake), mentor junior staff, and identify data-driven business opportunities.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

As a Growth Data Engineer, you will build and manage marketing data and attribution systems, ensuring reliable data flow and accurate measurement of acquisition efforts. The role involves collaboration across product, marketing, and data teams with a focus on optimizing campaign performance.

The Founding Data Engineer will design and build OpenArt's core data platform, ensuring data reliability, consistency, and scalability to support leadership and product metrics.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

As a Senior Data Engineer, you'll design scalable data models, manage cloud pipelines using Google Cloud services, and optimize data architecture while collaborating with cross-functional teams.

As a Senior Associate in Audit and Assurance, you'll evaluate AI solutions, manage AI/ML controls, and enhance transparency in reporting. Responsibilities include data analysis for governance strategies, guiding compliance practices, and contributing to innovative thought leadership in AI governance.

Lead the design and implementation of enterprise AI/ML solutions, oversee project performance, mentor leaders, and ensure compliance with Responsible AI.

The role involves designing and implementing AI/ML solutions, leading teams, mentoring staff, and managing project delivery while ensuring client satisfaction.

As a Software Engineer III at GlossGenius, you will lead data engineering efforts, designing and implementing data models and pipelines while mentoring engineers and shaping the data platform's vision.

The Analytics Engineer will design data models, build pipelines, and ensure data quality to support AI evaluation and insights.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

The Founding Data Engineer will manage the company's data models, ensure metric integrity, and work with various teams to deliver reliable metrics and reporting systems.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Staff Software Engineer will design, develop, and maintain scalable cloud-based solutions, manage data ingestion and retrieval, and lead architectural innovation while collaborating with cross-functional teams.

Design and develop Python-based analytics tools for investment research and portfolio analysis, while managing data lakes and AWS solutions.

Build and automate large-scale ML data pipelines and tooling for autonomous trucking. Improve dataset curation, deduplication, labeling, evaluation, and metrics infrastructure. Collaborate with robotics, autonomy, and infra teams to support continuous learning, deployment, and scalable AI infrastructure for Kodiak's fleet.

The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.