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Build and maintain a cloud-scale data lake and ETL pipelines on AWS for a major bank’s AI and analytics platform using PySpark and Java.
Build and maintain cloud-based data pipelines in Python and SQL, design modern data platforms (Data Lake, Warehouse), and ensure data quality and observability for analytics and AI projects.
Senior Data Engineer builds and maintains a data lake and AI/ML platform, designing data management tools and ensuring compliance while collaborating with research teams.
Build and maintain large-scale data pipelines and warehouses for a retail-focused analytics platform using GCP BigQuery, SQL, Python, and DevOps practices.
Build and maintain scalable data pipelines using dbt and SQL to model and transform enterprise data for analytics and reporting in a modern data warehouse.
Design and build scalable cloud data pipelines on Google Cloud Platform (BigQuery, Dataflow, etc.) to enable AI-driven analytics and business intelligence for enterprise clients.
Build data pipelines and interactive tools to automate analyses for drug discovery, using Python/Java/Scala/C++ and cloud platforms like AWS/GCP.
Build and maintain a reliable data infrastructure, automate pipelines, and create dashboards to support decision-making and self-service analytics for a fast-growing edtech startup.
Build and maintain Big Data pipelines on GCP for a major retail client, using BigQuery, SQL, Python, and DevOps practices to support data analysts and ensure operational reliability.
Design and build large-scale data pipelines on Azure/Databricks using PySpark, ensuring quality and performance for a major electricity distributor.
Designs and builds scalable data pipelines, cloud data architectures, and ETL/ELT processes for AI and ML projects at major enterprise clients.
Build and maintain scalable data pipelines, integrate diverse sources, and support analytics teams with Python/R scripts and cloud-based ETL workflows.
Build and maintain scalable data pipelines, optimize Big Data architectures, and ensure data quality and governance for analytics and decision-making.
Design scalable data architectures and MLOps pipelines, industrialize ML models, and ensure data quality for enterprise AI projects in cloud environments.
Design and build scalable cloud data pipelines on GCP (BigQuery, Dataflow, etc.) for enterprise clients, ensuring DataOps and DevOps best practices.
Build and maintain scalable data pipelines and warehouses in GCP/Azure, transforming raw data into clean, reliable insights for business decisions and dashboards.
Build and optimize robust, scalable data pipelines and architectures for enterprise clients, blending hands-on engineering with consulting to turn business needs into actionable data solutions.
Build and maintain end-to-end data pipelines on Azure Data Factory and Microsoft Fabric, integrating large-scale data from APIs and databases to support airline operations.
Build and maintain robust data pipelines on Google Cloud for analytics and AI clients, using BigQuery, Dataflow, Pub/Sub, and Airflow to process batch and streaming data at scale.
Design and maintain data architectures, SQL models, and ETL/ELT pipelines for a medical-sector client’s cloud platforms.
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