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Data Engineer( Microsoft Fabric) @ Capgemini Polska Sp. z o.o.
Build and maintain Microsoft Fabric pipelines and data models, using PySpark and Azure tooling to move raw data through bronze, silver, and gold layers for analytics.
Senior Data Engineer (Databricks) @ CLOUDFIDE SP. Z.O.O
Build and scale cloud data platforms for global clients using Azure, Databricks, Spark, and CI/CD pipelines, designing ETL/ELT architectures and data models.
Lead Data Engineer: GCP & PySpark, Fully Remote
Lead Data Engineer designs and migrates data pipelines using GCP and PySpark, guiding a remote team and ensuring robust data infrastructure.
Data Engineer with Microsoft Fabric (f/m/x)
Build and maintain enterprise data platforms using Microsoft Fabric, Azure Data Lake, and PySpark to integrate financial, sales, and operational data for analytics and reporting.
Senior Data Engineer – PySpark, Hadoop & Airflow (Hybrid)
Designs and builds scalable data pipelines using PySpark, Hadoop, and Airflow in a DevOps environment to support analytics and reporting.
Junior Data Engineer - Hybrid, Python/SQL ETL
Builds and monitors a Microsoft-Fabric-based data warehouse, writes PySpark and T-SQL ETL/ELT pipelines, and collaborates with Power BI teams to deliver business-facing analytics.
Data Engineer (Microsoft Fabric) @ Mindbox Sp. z o.o.
Design and build ETL/ELT pipelines and data models using Microsoft Fabric (Data Factory, Lakehouse, Synapse) and Power BI to deliver enterprise reporting solutions.
Lead Data Engineer (GCP / PySpark) @ Michael Page
Lead a data engineering team to build and migrate media-industry data platforms on GCP using PySpark, while removing technical blockers and guiding architectural decisions.
Senior Data Engineer (with GCP experience) - ICH Europe
Design and build scalable data pipelines on GCP (BigQuery, Cloud Composer) to feed AI/ML models, using Python, SQL, dbt and Data Vault 2.0.
Senior Data Engineer (with GCP experience) - ICH Europe
Build and maintain scalable data pipelines on GCP for AI initiatives, using Python, SQL, dbt, and BigQuery to enable large-scale analytics and ML workloads.
Senior AI Data Engineer (AI/Data Platform, Cloud Technologies, Python)
Design and build scalable cloud-native AI data platforms and pipelines using Python, Spark, and Kafka to power machine learning and GenAI initiatives for enterprise clients.
Senior Data Engineer - financial industry (f/m/x)
Build and optimize scalable data pipelines using Databricks, PySpark, and Azure for a modern fintech data platform.
Senior Data Engineer – automotive sector (f/m/x)
Senior Data Engineer builds and maintains cloud-based data pipelines and lakes for a global financial-services client, using Azure Databricks, PySpark, and Azure SQL to enable analytics.
Data Engineer (PySpark) for AI & Big Data
Design and build PySpark-based data pipelines in distributed environments, transforming large datasets and collaborating with architects and analysts to deliver high-quality data solutions.
Data Engineer z GCP (f/m/x)
Build and maintain scalable data pipelines on Google Cloud Platform, focusing on BigQuery, Airflow, and Terraform to process and transform large datasets for analytics and ML.
Data Engineering Consultant (Cloud & AI) - ICH Europe
Design and build scalable cloud data pipelines and ETL workflows using PySpark, SQL, and cloud platforms (AWS/Azure/GCP) to support AI-driven analytics for global enterprise clients.
Junior Mid-Level Machine Learning Data Engineer
Build and maintain data pipelines and infrastructure for AI solutions, working with Spark, Python, and LLMs to support machine learning models and predictive analytics.
Hybrid Data Engineer (Kraków): Cloud ETL & Analytics
Build and maintain cloud-based ETL/ELT pipelines and data platforms using Python, SQL, and Spark to deliver analytics-ready data for business decisions.
Senior Data Engineer: AML Platform Migration (Remote)
Senior Data Engineer to migrate and centralize an AML data platform using Python, PySpark, Databricks, and ETL pipelines for a banking client.
Senior Data Engineer (Python | Databricks | Cloud) @ 1dea
Build and maintain scalable cloud data pipelines and architectures using Python, Databricks, and AWS/Azure/GCP, following DevOps practices and the full software development lifecycle.