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GCP Data Engineer - Customer Value and Digital Engagement Department
Design, build, and maintain GCP-based data pipelines (ETL/ELT) and warehouses to power analytics, ML models, and AI apps for a telecom company.
Data Engineer – AI-Accelerated Development for Modern Data Platform
Build and maintain scalable ELT/ETL pipelines, orchestrate workflows in Airflow, and model data in Snowflake/Databricks to power analytics and AI apps, using Python, SQL, and AI coding tools.
Big Data Engineer (Spark/Scala/Java)_WROCLAW OR KRAKOW
Build and maintain a scalable big-data platform on Azure Databricks using Spark, Scala, and Java, enabling teams to run analytics and regulatory workloads.
Senior Data Engineer: Spark, Java/Scala, ETL - Hybrid Kraków
Build and maintain ETL pipelines using Spark, Java, and Scala for clients across industries, focusing on clean code and modern engineering practices.
Senior/ Lead Data Engineer with industrial knowledge (Freelancer) @ Spyrosoft
Design and implement data pipelines from industrial systems (MES, SCADA, historians) into clean, auditable datasets, then build PoC analytics and visualizations to validate KPIs for chemical-process digitalization projects.
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 (Python / Apache Spark / Azure) @ Square One Resources
Builds and optimizes Apache Spark pipelines on Azure/Databricks to process tax-related data, using Python and columnar formats like Parquet/Delta.
Data Engineer with AWS Python, SQL, AWS, ETL/ELT, CI/CD
Build and maintain scalable AWS-based ETL/ELT pipelines using Glue, Spark, and SQL to feed data warehouses and analytics.
Big Data Engineer Intern — 6-Month Paid, Flexible 30h/wk
6-month internship building big-data pipelines and analytics with Java/Scala/Python and Spark for Fortune 1000 clients under mentor supervision.
Senior Data Engineer Apache Hadoop, Apache Spark, SQL, Kafka Gdańsk
Build and maintain distributed data pipelines for regulatory reporting using Hadoop, Spark, SQL, and Kafka, while ensuring data quality and system stability.
Senior Data Engineer Apache Hadoop, Apache Spark, SQL, Kafka Gdańsk
Build and maintain distributed data pipelines using Hadoop, Spark, SQL, and Kafka to support regulatory reporting and event-driven architectures.
Data Engineer – Cloud ETL & Databricks (Marketing Data)
Design and implement scalable cloud ETL pipelines using Databricks, Spark, and Python to power marketing analytics for a global FMCG client.
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.
Senior Big Data Engineer (Databricks + AWS) @ SoftServe
Design and maintain scalable batch and streaming data pipelines using Databricks, AWS, PySpark, and Kafka for large-scale data processing.
Data Engineer (Senior/Mid) @ Harvey Nash Technology
Build and maintain big-data pipelines in Python/Spark/Scala, design cloud infrastructure, and collaborate with researchers to deliver end-to-end data solutions.
Data Engineer - Hybrid (Warsaw) | Big Data, Spark & CI/CD
Builds and maintains scalable data pipelines using Spark, Scala, and ETL processes, with SQL and BI tools like Databricks and Power BI.
Big Data Engineer (Python/Spark) for Banking Data
Build and enhance Big Data solutions for a banking client using Python and Apache Spark, processing large-scale financial datasets.
Senior Data Engineer - Hadoop, Spark, SQL & Kafka
Builds and maintains distributed data pipelines for regulatory reporting using Hadoop, Spark, SQL, and Kafka.
Spark/Scala Big Data Engineer — Hybrid in Warsaw
Builds and maintains a new big-data platform for structured finance using Spark and Scala, ensuring data quality and supporting digital strategy.
Senior Data Engineer with German | f/m/d
Build and deploy scalable data pipelines and MLOps workflows to integrate structured, semi-structured, and unstructured data for GenAI and LLM solutions in the insurance sector.