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Build and maintain distributed data pipelines and processing systems for a Vulnerability & Exposure Management Platform, handling millions of daily events with Python, PySpark, and cloud tools.
Design and build data platforms in Azure and on-premises, integrating data pipelines for clients in automotive, life sciences, finance, or manufacturing using SQL, Python, and DevOps.
Design and build data platforms in Azure and on-premises, integrating data for clients in mobility, healthcare, finance, or manufacturing using SQL, Python, and DevOps.
Designs scalable data architectures (Data Lake/Warehouse) and builds batch/real-time pipelines using modern platforms like Databricks or Microsoft Fabric, cloud (Azure/AWS/GCP), SQL and Python.
Design and build scalable Azure Databricks data pipelines for HR datasets, focusing on automation, testing, and production-quality analytics in a hybrid London setup.
Build and maintain scalable Azure Databricks data pipelines and analytics for HR tech, using Spark, SQL and Azure services to automate employee lifecycle data flows.
Build and deploy AI systems for a Saudi real-estate platform: integrate LLMs, design RAG pipelines, and ship production-ready analytics tools for commercial, retail, and residential portfolios.
Build and maintain ETL pipelines and data systems using Python, Airflow, Spark, and PostgreSQL to process geospatial data for a next-gen mapping platform.
Build and maintain the data pipelines and retrieval layer that power Mirai’s Generative AI products on AWS, including vector stores, embeddings, and governed datasets.
Build and maintain data quality frameworks and pipelines, enforcing standards across systems and mentoring teams to ensure reliable enterprise data.
Design and maintain data quality frameworks, rules, and automated checks to ensure enterprise data accuracy and reliability across systems.
Designs and governs enterprise-scale data architecture, models, and integration frameworks to support analytics and business transformation using TOGAF/DAMA standards.
Design and deliver modern data platforms for clients, assessing architecture maturity and defining roadmaps for governance, migration, and cloud enablement in a consulting role.
Design and build scalable ETL/ELT pipelines and real-time dashboards for industrial digitalization in oil & gas, petrochemicals, utilities, and manufacturing using Hadoop/Cloudera, PySpark, and BI tools.
Design and maintain scalable data pipelines and ETL processes using Spark, Kafka, and Airflow, and optimize data storage in cloud warehouses and lakes to support analytics and ML initiatives.
Design and maintain scalable ETL/ELT pipelines and data infrastructure using Apache Spark, Airflow, and Data Lake architectures to enable analytics and business decisions.
Build and maintain a secure, scalable data API for a fintech startup in Mexico using Python/Node.js, React.js, REST/GraphQL, and AWS.
Build and maintain large-scale data pipelines and ETL components in Java/Scala, using Spark for batch/streaming processing to support enterprise clients in media, healthcare, and tech.
Design and build data pipelines and warehouses using Microsoft Fabric, Azure Synapse, and Power BI for enterprise clients, ensuring performance, governance, and security.
Build and maintain Python-based data pipelines, REST APIs, and automation tools to process, clean, and expose data for analytics and internal tools.
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