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Builds clean, reusable Python components for a data platform that ingests, transforms, and powers data-driven products.
Build and maintain a cloud-agnostic platform for data ingestion, processing, and ML workflows, collaborating with data scientists to ensure scalability and reliability.
Build and optimize high-performance data pipelines for crypto trading, ingesting and processing market data with Python, Rust, and distributed systems like Kafka and ClickHouse.
Build and maintain ETL pipelines, data quality systems, and new data products using Python, SQL, Spark, and AWS tools to power Leadinfo’s B2B lead-gen platform.
Build and maintain real-time data pipelines and self-serve tooling for a fintech firm’s trading, risk, and analytics platforms.
Builds and maintains a secure, scalable data platform for medical data and AI models using Python and Terraform, ensuring compliance with privacy regulations.
Build and maintain a cloud-agnostic data and ML platform for scalable, reproducible model training and deployment across multiple products, ensuring reliability, cost-efficiency, and EU compliance.
Build and maintain the data pipelines and AI infrastructure that turn employee feedback into actionable insights for HR teams worldwide.
Designs and maintains Splunk data pipelines for a DoD Zero Trust Edge project, focusing on edge processing, telemetry integration, and secure data transport for threat hunting.
Build and maintain the data pipelines and AI infrastructure that turn employee feedback into actionable insights for HR teams worldwide, using cloud-native tools and MLOps practices.
Build and maintain scalable data pipelines and AI/ML infrastructure, integrating diverse sources and deploying models using cloud-native tools like Azure.
Designs and maintains scalable data pipelines and MLOps workflows to feed AI models in a cloud environment.
Build and maintain scalable data pipelines on Azure and Databricks using Spark to transform raw data into insights for analytics and business use.
Design and maintain a secure, scalable data platform for multimodal medical datasets, enabling AI training and real-time hospital workflows using open-source tools like Kubernetes, Terraform, and Dagster.
Design and build scalable Azure data pipelines using Databricks, PySpark, and Azure services to process and transform enterprise data for analytics and migration projects.
Build and maintain scalable Azure data pipelines using Databricks, Data Factory, PySpark, and Python to power enterprise analytics and reporting.
Design and build scalable Azure data pipelines with ADF, Databricks, and PySpark, plus automate deployments using Azure DevOps and Bicep.
Build and optimize data pipelines for Fortune 500 clients using Azure, Microsoft Fabric, and Databricks, focusing on ingestion, transformation, and modeling.
Build and maintain data pipelines and infrastructure to support crypto trading and machine learning research in a fast-paced trading environment.
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