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Design and build scalable data pipelines, Data Lakes, and DWHs using BigQuery, Kafka, Airflow, and Kubernetes, with exposure to GenAI integrations.
Build and optimize large-scale data pipelines on Databricks using Python and cloud-native tools, ensuring scalable, secure data processing for enterprise clients.
Build and maintain Mettler Toledo’s data platform, creating scalable pipelines and ensuring high-quality data flows for analytics and AI/ML using Databricks, Snowflake, and Python.
Build and maintain data pipelines and warehouses using Oracle, PostgreSQL, BigQuery, Informatica PowerCenter, Kafka, and Python to feed analytics and ML workloads.
Build and maintain scalable data pipelines for large enterprises using Spark, Cloudera, and Airflow to process streaming and batch automotive, aerospace, and telecom data.
Senior Azure Data Engineer designs and builds scalable data pipelines using Azure Data Factory, Databricks, and Synapse Analytics to support real-time and batch processing for global IT systems.
Senior Python Data Engineer builds and maintains scalable data pipelines and models for regulatory reporting in finance, using Python, Spark, and Databricks to process high-volume batch and streaming data.
Build and automate predictive models, ETL pipelines, and monitoring systems using Python, Databricks, and Azure to power AI-driven marketing analytics and campaign optimization.
Design and maintain Azure-based security data pipelines, ETL processes, and analytics platforms to centralize and secure enterprise data across multi-cloud environments.
Build and optimize scalable HR data pipelines on Azure Databricks using Spark, SQL, and DevOps practices to power analytics and employee-facing products.
Designs and builds scalable data lake and warehouse solutions using SQL, Python, and cloud tools like Google Cloud Platform and Informatica Power Center.
Design and implement Azure Data Lake and Data Warehouse solutions using Python, SQL, Databricks, and event processing; mentor junior engineers in a hybrid work model.
Build and maintain scalable Azure-based ETL/ELT pipelines to integrate enterprise systems and transform raw data into analytics-ready insights for reporting.
Build and modernize Big Data pipelines for a European scoring agency using Azure Data Factory, Python/Java, and streaming tech like Kafka.
Design and build a scalable enterprise search engine for a global financial firm using Python, Spark, and Azure services.
Design and build Azure-based data pipelines, warehouses, and analytics using Databricks, Data Factory, and Power BI to process large datasets and enable ML workloads.
Designs and maintains scalable data pipelines and a central data platform using Databricks and Snowflake to power analytics and AI/ML across the organization.
Designs and maintains scalable data pipelines and a central data platform using Databricks, Snowflake, and Python to power analytics and AI/ML across the organization.
Design and implement Microsoft Fabric and Azure-based data pipelines, ETL/ELT processes, and AI-driven analytics solutions for enterprise clients.
Build and optimize Azure Data Factory/Synapse pipelines and Microsoft Fabric solutions, integrating AI-powered analytics and Power BI models to deliver business insights for clients.
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