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GCP Data Engineer — Build Scalable ETL Pipelines
Build and optimize GCP-based ETL/ELT pipelines using BigQuery and Dataflow for enterprise clients in Spain.
Data Engineer: Microsoft Fabric & Azure Pipelines (Hybrid)
Builds and maintains end-to-end data pipelines using Microsoft Fabric, Azure Data Factory, and Spark/Databricks for batch and near real-time analytics.
Data Engineer – Vulnerability Data Platform (Hybrid)
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.
Cloud Data Engineer: AWS & Snowflake Pipelines
Designs and maintains AWS-based ETL/ELT pipelines, optimizes Snowflake data models, and builds Airflow workflows to deliver trusted datasets for analytics and BI.
Data Engineer Remoto y Horario Flexible - Pipelines en la Nube
Build and maintain cloud-based data pipelines using ETL/ELT, SQL, Python, dbt, Airflow and Spark in a flexible, autonomous role.
AWS Data Engineer: ETL Pipelines, Redshift & BI
Build and maintain data ingestion and ETL/ELT pipelines using Python, PySpark, and Spark, then deliver analytics via Redshift and BI tools.
Senior Data Engineer
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.
Data Engineer AWS
Builds and maintains AWS-based data pipelines using Glue, Spark, Lambda, and S3 to move and transform data for analytics and reporting.
Remote Data Engineer — ETL & API Pipeline Architect
Design and maintain ETL/ELT pipelines and API integrations to unify data sources into a reliable foundation for analytics and business teams.
Data Engineer
Build and maintain scalable data pipelines using Databricks, Azure Data Factory, and PySpark to process and transform enterprise data for analytics and reporting.
Senior Data Engineer: Cloud Pipelines & ML
Build and maintain cloud data pipelines and ML solutions using Python, SQL, and dbt on Google Cloud, AWS, and Azure.
Data Engineer — Build AI-Ready, Scalable Data Pipelines
Build and optimize enterprise-scale data pipelines for AI readiness using SQL, Linux, and ETL/ELT tools in a cloud environment.
GCP Data Engineer: Cloud Pipelines & Data Governance
Designs and builds GCP-based ETL/ELT pipelines and data governance workflows using BigQuery, Dataflow, Dataproc, Airflow, and Pub/Sub.
Junior Data Engineer – Mobile Apps & Cloud Data Pipelines
Build and maintain cloud data pipelines on GCP and Databricks, using BigQuery, Airflow, dbt, and Dataflow to feed dashboards and experiments.
AWS Data Engineer: Build Data Pipelines & Redshift
Build and maintain data ingestion and transformation pipelines using AWS, S3, Redshift, PySpark, and SQL to process structured sources and files.
Senior Data Engineer: ELT Pipelines & Data Platform
Design and scale high-performance ELT pipelines and data platforms using SQL and Python for a product-focused data engineering team.
Remoto Data Engineer: Pipelines, BigQuery & GCP
Builds and optimizes ETL/ELT pipelines on GCP, models data in BigQuery, and applies cost-efficient engineering practices for analytics workloads.
Senior Data Engineer - AI-Powered Data Pipelines
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.
Data Engineer: Build Scalable Data Pipelines in Cloud
Build and optimize multi-cloud data pipelines using SQL, Python, and ETL/ELT tools while collaborating with clients and internal teams.
Senior Python Developer - Remote EU, Banking Transformation
Build and maintain scalable data platforms for a bank’s transformation using Python, SQL, and cloud tools, with ETL/ELT pipelines.