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Maintain and evolve a hybrid (on-prem + cloud) Kubernetes infrastructure for a fintech company, automate deployments with GitLab CI/CD, and collaborate with dev teams on scalable payment solutions.
Lead a data engineering and analytics team to build scalable data infrastructure and AI-powered analytics for Serve Robotics' autonomous delivery robots, enabling data-driven decisions across operations and product.
Build and scale ZoomInfo’s data platform, designing pipelines and storage layers that power AI/ML training, real-time products, and analytics for GTM intelligence.
Build and maintain high-performance data infrastructure for AI workloads, handling petabyte-scale storage and processing with distributed frameworks like Spark and Kubernetes.
Principal Data Engineer designs and maintains scalable, self-hosted data pipelines and databases for a game studio, ensuring robust performance and compliance.
Build and maintain the data pipelines and tooling that feed AI/ML services for a cloud-based healthcare platform, enabling model development, deployment, and monitoring at scale.
Build and maintain high-performance data pipelines in Snowflake and AWS, using dbt Core/Cloud and Python to power analytics and AI initiatives for an insurance company.
Build and own the data pipelines, ML feature stores, and inference APIs that power renewable-energy analytics at scale, integrating forecasts into a SaaS platform for wind, solar, hydro, and storage assets.
Lead a team to design and build scalable data pipelines on Hadoop/Databricks and cloud platforms, enabling analytics and GenAI/LLM-ready data ingestion for enterprise clients.
Build and scale face-recognition systems using PyTorch/TensorFlow, own end-to-end ML pipelines on AWS, and lead fairness analysis for biometric models in production.
Design and build scalable data pipelines and architectures for EA Sports FC, using Python, Spark, Kafka, and AWS to deliver analytics and AI-driven insights.
Senior Data Engineer at Apple builds and maintains data pipelines and products for the App Store using Java/Scala, SQL, Kafka, and Airflow to drive marketplace insights.
Build and maintain petabyte-scale storage infrastructure for AI training workloads, optimizing data pipelines and distributed systems for performance.
Build and productionize LLM-powered AI agents and orchestration systems using NLP, retrieval-augmented generation, and agent workflows to enhance customer-experience analytics.
Build data pipelines, automation tools, and metrics to accelerate AI-first self-driving development and simulation workflows.
Design and maintain scalable data pipelines using Python, SQL, Databricks, Snowflake, and cloud tools; lead a team of data engineers to deliver AI-driven marketing solutions.
Lead the design and maintenance of Databricks-based ETL pipelines and data models for a fintech platform, transforming raw financial data into insights for investors and AI workloads.
Build and maintain large-scale data pipelines and products for the App Store, processing petabytes daily to generate insights while ensuring privacy and correctness.
Builds and maintains scalable ETL pipelines and data warehouses to power analytics for EA’s user-generated content platform, using Python, SQL, Airflow, and cloud platforms.
Build and optimize ETL/ELT pipelines using AWS and Snowflake to support analytics and governance in a wealth-tech environment.
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