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Cyrantos is partnering with a leading asset management firm to find a highly experienced Senior Data Engineer to join their team. This is a remote position with a start date as soon as the candidate successfully…
As a founding data engineer, you will design and build a scalable data platform from the ground up to support mobile game analytics, LiveOps, and marketing. You will utilize technologies like Python, SQL, AWS, dbt, and Airflow to create robust data pipelines and infrastructure.
The Senior Data Engineer will design and maintain scalable ETL/ELT pipelines and data solutions within an Azure environment. The role focuses on utilizing Azure Databricks, Azure Data Factory, PySpark, and SQL to support global analytics initiatives.
The Senior Data Engineer will design, build, and maintain scalable data pipelines and platforms using Python, PySpark, and GCP technologies. This role involves collaborating with cross-functional teams to automate data processes and implement modern software engineering practices.
The Data Engineer will migrate and modernize ETL processes and Oracle data structures to Azure using Microsoft Fabric. The role involves building analytical models in PowerBI, optimizing performance, and maintaining data pipelines.
The Data Engineer will design and implement batch and streaming data pipelines, manage ETL/ELT processes, and ensure data quality. The role requires proficiency in Python, Java, or Scala, along with experience in Spark, SQL, and cloud platforms like AWS.
Designs and builds cloud-based data platforms (warehouses, lakes) using Azure tools, ensuring data quality, governance, and seamless ETL pipelines while collaborating with stakeholders to modernize legacy systems and support AI/ML use cases in sectors like retail, manufacturing, and finance.
This Senior Data Engineer role involves building data-quality frameworks and high-throughput pipelines for fraud detection and AML systems within a European fintech company. The position requires deep domain expertise in transaction monitoring and strong Python skills to support automated decision engines.
The Data Engineer will design, implement, and maintain scalable data pipelines and ETL processes within Azure and Databricks environments. The role involves collaborating with cross-functional teams to build big data solutions and ensure high-quality data standards.
The Junior Data Engineer will join the AI Markets team to develop and optimize kdb+ time-series databases, building analytic layers and APIs for traders and quants. The role involves working with large datasets, performance tuning, and integrating data with AI/ML workflows.
The Data Engineer will migrate and modernize ETL processes and Oracle data structures to Azure using Microsoft Fabric, while developing analytical models in PowerBI. The role requires advanced Python and SQL skills, experience with Azure cloud services, and the ability to work in a hybrid model in Warsaw.
Data Engineer designing and maintaining real-time data pipelines on GCP for a streaming platform, using Terraform, Kubernetes/GKE, and observability tools.
Build and orchestrate production-grade data pipelines and Data Lake/DWH solutions on Google Cloud Platform using Python, SQL, BigQuery, and Airflow in a hybrid role based in Kraków.
Senior Data Engineer designing scalable backends and data pipelines within a microservices architecture, using Java, C#, Go, or Python with Airflow/ETL in cloud environments.
Senior Data Engineer builds and maintains scalable fraud and AML data pipelines in Python to power real-time decision engines.
Data Engineer designing and implementing data pipelines using Data Factory, PySpark, and Microsoft Fabric, collaborating with business teams and the Risk Unit in a hybrid role in Warsaw.
Data Engineer maintaining and evolving a Microsoft Fabric platform, building bronze/silver/gold medallion-architecture pipelines and data models using PySpark and Spark SQL.
Data Engineer building and maintaining ELT pipelines and data warehouses using AWS (S3, Redshift), dbt, Airflow, and SQL.
This role involves leading end-to-end data engineering initiatives to support AI use cases, including building ELT pipelines and maintaining dbt models. The position requires extensive experience with Snowflake, Azure, and Python to deliver scalable analytics datasets.
Build and maintain scalable data pipelines for corporate lending using Python, PySpark, and SQL to transform data into analytics and insights.
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