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Senior BI Developer designing, building, and optimizing data intelligence solutions using Microsoft (Power BI, Fabric) and IBM (Cognos, DB2) platforms, with heavy emphasis on T-SQL, ETL, data warehousing, and data modeling to support strategic decision-making.
Senior ML Engineer building self-service ML platform tooling—model packaging, deployment, CI/CD, and observability—using Python, PyTorch, TensorFlow, Docker, Kubernetes, MLflow, and GitHub Actions at a lottery and sports betting company in Toronto.
Leads AI/data engineering solutions on RBC’s hybrid multi-cloud platform, designing scalable pipelines, RAG systems, and agentic workflows to meet business objectives. Mentors teams and ensures robust, governed data products for financial AI applications.
Cloud Data Engineer (5+ years) to configure cloud environments and build data pipelines using Azure Synapse, ADF, Databricks, and Spark Our transportation client is seeking a Cloud Data Engineer (5+ years) to configure…
Descripción del puesto: Buscamos un/a Data Engineer especializado en PySpark y Python para incorporarse a proyectos de Big Data en entornos Cloud, con responsabilidad en mantenimiento correctivo y evolutivo, gestión de…
Design, develop, and maintain data pipelines using Databricks on Azure and AWS with Python, PySpark, and Pandas, working within Agile/DevOps teams on client projects.
Senior Data Engineer building and maturing a scalable Azure/Databricks data platform for an accounting and advisory firm in Utrecht, developing PySpark/SQL pipelines, data models, and CI/CD workflows.
Senior Data Engineer in Amsterdam focusing on designing and operating high-quality data pipelines on a Big Data Platform, collaborating with stakeholders, and championing data best practices. Core technologies include Python, PySpark, Airflow, Hadoop, Spark, Kafka, and SQL.
Build and maintain scalable ELT data pipelines using Python, PySpark, Airflow, Hadoop, and Spark for a Big Data Platform.
Senior Data Engineer building scalable data platforms and pipelines using Python, PySpark, and SQL on a lakehouse architecture within VodafoneZiggo's Data & AI team, in a hybrid work setup.
The Principal AI Engineer will lead the design and implementation of agentic AI systems and data platforms within a financial services environment. The role involves building RAG solutions, scalable data pipelines, and AI observability frameworks using technologies like Python, Spark, and Databricks.
This role involves administering Databricks ecosystems and developing robust data processing solutions using Python to support enterprise analytics. The position requires extensive experience in Databricks platform management, performance optimization, and data engineering practices.
The Principal Data Engineer will design and implement a scalable data platform using Snowflake and related technologies to support data governance and analytics. The role involves leading data strategy, optimizing ELT pipelines, and enabling AI adoption within an Agile environment.
Python backend developer for an ad tech company's flagship Ad Suite product, building and maintaining scalable cloud applications using Python and AWS services (Lambda, S3, DynamoDB, etc.) in a microservices architecture.
Designs and maintains scalable data platforms on Azure and Databricks, focusing on ETL/ELT pipelines, data lakehouse architecture, and cloud-native migrations while ensuring data quality, governance, and DevOps automation.
The Senior Data Engineer will build and optimize large-scale data processing engines using Spark, PySpark, and Python within a cloud-based lakehouse environment. The role focuses on modernizing legacy SQL ETL logic into modular Python libraries and implementing medallion architecture.
The Data Engineering Lead will design, build, and manage enterprise-scale data platforms and pipelines to support business intelligence and analytics. The role involves technical leadership, mentoring, and ensuring data quality and security using cloud-native technologies like AWS, Azure, Snowflake, and Databricks.
Design, develop, and optimize enterprise-scale data solutions on Cloudera CDP and Hadoop, building ETL pipelines with Spark, PySpark, NiFi, Sqoop, SQL, Python, and shell scripting in a Linux environment.
Build and maintain large-scale data pipelines using Cloudera, Hadoop, Spark, and SQL to process and analyze enterprise datasets for smarter business decisions.
Inetum is seeking a Data Engineer to design and industrialize data pipelines using Databricks, PySpark or Scala, and Delta Lake. The role involves working on batch and streaming dataflows within cloud environments using DataOps practices.
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