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Senior Data Engineer: Cloud Pipelines & ML
Build and maintain cloud data pipelines and ML solutions on GCP, AWS, and Azure using Python, SQL, dbt, and API-first architectures.
Data Engineer
Build and optimize data pipelines (ETL/ELT) in Azure to integrate and clean hotel and guest data, enabling analytics and Power BI dashboards for business decisions.
Data engineer
Build and maintain robust ETL/ELT pipelines, cloud data warehouses/lakes, and curated datasets for BI and AI initiatives using Snowflake, Azure, or AWS.
Senior Data Engineer - AI-Powered Data Pipelines
Build and optimize scalable ETL/ELT pipelines, populate data warehouses and lakes, and secure tenant data for AI-powered analytics across Emburse’s products.
Data Engineer: Build Scalable Data Pipelines in Cloud
Build and optimize scalable, multi-cloud data pipelines using SQL, Python, and ETL/ELT tools while collaborating with clients and internal teams.
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 AWS-based data pipelines that ingest and transform structured data into Redshift using PySpark, SQL, and ETL/ELT tools.
Senior Data Engineer - End-to-End Azure Data Pipelines
Build and maintain Azure-based data pipelines for a financial data platform, implementing ETL/ELT patterns and ensuring data governance.
Senior Data Engineer: ELT Pipelines & Data Platform
Designs and scales high-performance ELT pipelines and data platforms using SQL and Python to improve data quality and performance.
Data Engineer
Designs and builds scalable data pipelines on GCP for a capital-markets fintech, integrating financial data sources and optimizing warehouse/lake solutions.
Data Engineer
Build and optimize Azure-based data pipelines and ETL workflows using Synapse, PySpark, and Databricks to ingest and process large-scale datasets.
Data Engineer — Build AI-Ready, Scalable Data Pipelines
Build and optimize enterprise-scale data pipelines to feed AI-ready systems, using SQL, Linux, and ETL/ELT tools on AWS/Azure/GCP.
GCP Data Engineer: Cloud Pipelines & Data Governance
Designs and builds GCP-based ETL/ELT pipelines and data governance workflows using BigQuery, Dataflow, Airflow, and related tools.
Senior Data Engineer | Cloud Pipelines & Data Quality
Designs and builds cloud data pipelines and architectures using SQL, Python/Scala, and Spark to process and optimize ETL/ELT workflows in a hybrid environment.
Remoto Data Engineer: Pipelines, BigQuery & GCP
Build and optimize ETL/ELT pipelines on GCP, model data in BigQuery, and tune performance and cost. Occasional optional office presence in Madrid.
Data Engineer – Full-Stack Data Pipelines & Governance
Builds and governs full-stack data pipelines using PySpark and Palantir Foundry, focusing on ETL/ELT design and data security for enterprise clients.
Senior Python Developer - Remote EU, Banking Transformation
Builds and maintains scalable data platforms for a bank’s transformation using Python, SQL, and cloud tools, collaborating with senior engineers.
Python Developer & AI Agents Engineer
Build and deploy AI agents and automation pipelines in Python to streamline supply-chain compliance workflows for life-sciences companies, using dbt, Docker, and cloud platforms.
Data Engineer (Senior) - ETL (Python+Snowflake) - Remote, Latin América
Senior Data Engineer builds and maintains scalable ETL pipelines using Python, Snowflake, and Azure, focusing on cloud data warehousing and dimensional modeling.
Lead Data Engineering
Lead a team of trainees to build scalable GCP-based data pipelines using BigQuery, Airflow, and Dataflow, while mentoring junior engineers and enforcing data governance standards.