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Build and optimize cloud data pipelines and lake house architectures for a global iGaming provider, migrating on-prem systems to AWS/Azure and implementing Kafka-driven streaming pipelines.
You’ll ensure the reliability of Guidewire’s large-scale data platform on AWS, managing Kafka, Spark, and Kubernetes to support AI and analytics workloads while improving automation and incident response.
Design and maintain large-scale data pipelines using PySpark, Hadoop, and Azure services to process and transform semiconductor manufacturing data.
Design and build scalable data pipelines on Azure using PySpark, SQL, Airflow, and Kafka to deliver high-quality data products for Bosch’s large-scale platform.
Builds and maintains scalable finance data pipelines on GCP (BigQuery, Dataflow, Pub/Sub) to power reporting, FP&A, and analytics for McDonald's India, ensuring data reliability and governance.
Design and build scalable data pipelines and analytics infrastructure using Python, Spark, and AWS for large-scale data processing and real-time streaming.
Designs and builds end-to-end data pipelines and cloud data lakes for a Big 4 bank, using Python, Spark and Azure to create reusable data assets and support analytics.
KEY RESPONSIBILITIES 1. Database Design & Development Design develop and maintain robust database solutions using Oracle and advanced PL/SQL including stored procedures functions packages and triggers. Build and…
KEY RESPONSIBILITIES 1. Database & Report Solution Design Design and build enterprise-grade database solutions that meet complex business and technical requirements. Develop and maintain comprehensive reporting…
Build and maintain data virtualization solutions using the Denodo Platform, configuring virtual views and optimizing integrations with diverse data sources.
Build, train, and deploy ML models in Python using TensorFlow/PyTorch to solve business problems and maintain production systems.
Build and optimize PySpark pipelines on Cloudera for large-scale banking data, enabling reliable ETL and analytics that power critical financial applications.
Build and maintain Azure-based data pipelines using Data Factory, Spark, and Hadoop to enable analytics and reporting for Naviq’s big-data initiatives.
Designs and optimizes cloud-based data pipelines on Azure (ADF, Databricks, Synapse) to enable enterprise analytics, ensuring scalability, governance, and performance for large-scale data initiatives.
Designs and maintains scalable data pipelines and cloud-native platforms to ensure reliable, high-quality data for analytics, BI, and AI use cases using SQL, Python, and Azure.
Builds and maintains big data pipelines using Cloudera CDP, Spark, Hive, and Hadoop to support analytics and production systems.
Design and maintain scalable data pipelines and infrastructure to support AI, ML, and analytics initiatives for a global fintech trading platform.
Designs and builds scalable big-data pipelines using Spark, Hadoop, and Kafka, primarily in Java/Scala/Python, on AWS or Azure.
Design and build scalable big-data pipelines using Spark, Hadoop, and Kafka to process and deliver actionable insights for a tech company in the UAE.
Designs and operates cloud infrastructure for AI solutions, automating CI/CD pipelines with Docker, Kubernetes, and Terraform while ensuring system reliability.
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