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Global M is seeking a Forward Deployed Engineer to build production-grade AI agents and data pipelines while collaborating directly with enterprise clients. The role focuses on delivering measurable ROI through AI and data solutions within a fast-paced, remote environment across European time zones.
The Lead Data Engineer will oversee the technical design and evolution of data architectures using Data Vault 2.0. The role involves translating functional requirements into technical solutions, mentoring the engineering team, and ensuring data traceability and quality across the entire pipeline.
The Senior Data Engineer will design and maintain data pipelines and analytical models within the Microsoft Azure ecosystem. The role focuses on building scalable data solutions using Azure Databricks, Data Factory, and advanced SQL and Python programming.
The Forward-Deployed AI & Data Engineer works directly with customers to solve real-world problems while contributing to the development of the company's core AI product. The role involves a mix of customer-facing work and hands-on software engineering using Python and SQL.
Data Engineer working on data transformation and BI for a leading multinational insurance company, using SQL, Python, PySpark, and Power BI to manage the full data cycle and deliver analytical solutions.
The Data Engineer will design and optimize scalable data pipelines using Snowflake and Azure, focusing on automation, security, and governance. The role involves building dbt models, managing Airflow DAGs, and implementing CI/CD workflows within an Agile team.
The Senior Data Platform Engineer will evolve data platforms on AWS by designing robust pipelines and automating environments using DevOps and Infrastructure as Code practices for a retail pricing SaaS.
The Data Engineer will design and implement cloud architectures and integrate ETL processes to provide data solutions for clients at Merkle. The role focuses on data infrastructure and requires proficiency in Linux, data processing, and DevOps tools.
The Data Engineer will design and maintain scalable batch and real-time data pipelines for a large-scale European customer loyalty app. The role involves managing massive transactional data to support marketing segmentation and AI-driven analytics initiatives.
Senior Data Engineer designing and maintaining scalable data pipelines on Azure (Databricks, Data Factory) using Python/Spark, collaborating with Data Science and Analytics teams.
Global M is seeking a Forward Deployed Engineer to build data pipelines, AI agents, and evaluation frameworks while collaborating with enterprise clients to deliver AI-driven solutions. The role focuses on shaping the core product by solving real-world problems and ensuring ROI for customers.
Build production AI/data solutions, data pipelines, integrations, and evaluation frameworks while working directly with enterprise clients using Python and SQL.
Data Engineer designing cloud data solutions, building analytical models, and optimizing platforms using Snowflake and DBT in an Agile environment.
The Data Engineer will design and implement a Medallion architecture within Microsoft Fabric, developing pipelines for data ingestion and transformation. The role involves modeling data for analytics and processing large-scale datasets using Spark, Python, and SQL to support business decision-making.
Keepler is seeking a Data Engineer to implement data models, orchestration flows, and governance strategies using PySpark and Palantir Foundry. This is an on-site role focused on building data pipelines and ensuring data security and quality for clients.
The Data Engineer will design, develop, and maintain data solutions within the Microsoft Azure ecosystem, focusing on ETL/ELT pipelines and scalable data architectures using tools like Databricks and Synapse.
The Data Engineer/ML Engineer will design and operate end-to-end data and machine learning pipelines within the AI Labs team at Insud Pharma. The role involves collaborating with cross-functional teams to build scalable, robust ML solutions while adhering to regulatory standards and DevOps best practices.
The ML Data Engineer will design and maintain data and ML pipelines within the AI Labs team, collaborating with data scientists to deploy models into production. The role focuses on MLOps, software quality, and cloud infrastructure.
The Senior Data Engineer will work on digital transformation projects using Azure, focusing on building scalable data pipelines. Key technologies include Apache Spark, Databricks, MongoDB, and Delta Lake within a DevOps and Agile environment.
The Data Engineer will design and optimize data pipelines using Snowflake and Azure, manage Airflow DAGs, and automate processes with Python. The role involves working in an Agile environment to ensure data quality, governance, and scalability.
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