Design, build, and operate data integrations and backend services for real-time marketing and analytics.

Design and build scalable data processing systems for petabyte-sized datasets.

Ensure data privacy compliance and develop tools to anonymize sensitive data in big data systems.

Design, implement, and maintain data systems to transform pharmaceutical data for cost-saving insights.

Build and maintain data systems to transform pharmaceutical data for pricing insights and cost savings.

Building highly capable agents requires accurate and comprehensive data.

Build and maintain a scalable data platform, designing and implementing data systems and driving data adoption.

Shape a new data platform, driving product vision and execution with engineering teams.

Designs and implements data lake architectures to meet business objectives.

Design and lead data warehouse solutions, guiding teams on architectural decisions.

Design and develop scalable data platforms for powering API observability & security products.

Develop and maintain large-scale machine learning infrastructures and tools.

Designs and builds data infrastructure to support business intelligence and analytics.

Design and implement large-scale data pipelines using distributed processing frameworks to process billions of data points daily.

Expand the Developer tools that capture business events, operational data and third party data into the Lakehouse.

Lead the technical direction of data engineering projects, including architectural design, technology selection, and standards definition.

Manage a team to build distributed data systems, especially database systems internals.

Find and validate the quality of required data, write documentation and implement data governance bases.

Design and build data pipelines using Databricks Lakehouse.

Design and manage scalable Kafka-based data pipelines.