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Designs and builds scalable data platforms, lakehouse architectures, and ETL/ELT pipelines to support analytics and AI workflows in a hybrid, international team.
Design and build scalable cloud data pipelines using Azure Data Factory and Databricks, then model and optimize datasets for Power BI analytics and reporting.
Build and optimize GCP-based ETL/ELT pipelines using BigQuery and Dataflow for enterprise clients in Spain.
Builds and maintains end-to-end data pipelines using Microsoft Fabric, Azure Data Factory, and Spark/Databricks for batch and near real-time analytics.
Build and maintain a distributed data pipeline for a vulnerability management platform, processing large datasets in near real-time using PySpark, Airflow, dbt, and AWS.
Build and maintain cloud-based data pipelines using ETL/ELT, SQL, Python, dbt, Airflow and Spark in a flexible, autonomous role.
Build and maintain data ingestion and ETL/ELT pipelines using Python, PySpark, and Spark, then deliver analytics via Redshift and BI tools.
Build and maintain data pipelines and ETL workflows in Python, orchestrating data ingestion from multiple sources for an AI-powered fintech using Kubernetes, Airflow, and cloud platforms.
Builds and maintains AWS-based data pipelines using Glue, Spark, Lambda, and S3 to move and transform data for analytics and reporting.
Design and maintain ETL/ELT pipelines and API integrations to unify data sources into a reliable foundation for analytics and business teams.
Build and maintain reliable data pipelines and analytics infrastructure for a fast-growing second-hand marketplace, enabling pricing, catalog, and operational insights.
Designs and maintains cloud data pipelines and analytics platforms for food and beverage processing plants using Azure, Databricks, and time-series databases.
Build and maintain scalable data pipelines using Databricks, Azure Data Factory, and PySpark to process and transform enterprise data for analytics and reporting.
Build and maintain cloud data pipelines and ML solutions using Python, SQL, and dbt on Google Cloud, AWS, and Azure.
Designs and builds GCP-based ETL/ELT pipelines and data governance workflows using BigQuery, Dataflow, Dataproc, Airflow, and Pub/Sub.
Build and maintain cloud data pipelines on GCP and Databricks, using BigQuery, Airflow, dbt, and Dataflow to feed dashboards and experiments.
Build and maintain data ingestion and transformation pipelines using AWS, S3, Redshift, PySpark, and SQL to process structured sources and files.
Design and scale high-performance ELT pipelines and data platforms using SQL and Python for a product-focused data engineering team.
Build and optimize scalable ETL/ELT pipelines, populate data warehouses and lakes, and secure tenant data while enabling AI-driven analytics for Emburse’s products.
Build and optimize multi-cloud data pipelines using SQL, Python, and ETL/ELT tools while collaborating with clients and internal teams.
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