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Data Engineering Manager (Databricks)
Designs and maintains semantic data layers and KPI models using Databricks to enable governed executive dashboards and AI-driven analytics, collaborating with business teams to define and implement data-driven metrics and pipelines.
Data Engineering Manager (Databricks)
Designs and maintains semantic data layers and KPI models using Databricks to enable governed executive dashboards and AI-driven analytics, integrating multi-source enterprise data while ensuring quality, security, and governance.
Data Engineering Manager (Databricks)
Lead a team to design and maintain Databricks-based semantic layers and KPI models that power AI-driven analytics and executive scorecards, collaborating with business teams to translate requirements into governed data assets.
Group Product Manager - Bring Your Own Cloud
Lead a team to define and deliver Datadog’s Bring Your Own Cloud (BYOC) product, enabling customers to cost-effectively analyze petabytes of telemetry data in regulated, AI-first environments.
Développeur(se) IA/AI Engineer – Databricks
The AI Engineer will design, develop, and deploy scalable agentic AI systems and generative AI applications using the Databricks platform. This role involves collaborating with data scientists and engineers to integrate AI models into production environments while utilizing Python, SQL, and modern cloud architectures.
Junior Data Engineer (12-month Contract)
Builds and maintains data pipelines, scripts, and notebooks for regulatory decision-making, focusing on SQL/Python, data ingestion, transformation, and documentation under senior guidance.
Databricks Data Engineer
The Databricks Data Engineer will design, build, and maintain data pipelines and architectures using the Databricks platform and cloud services. This role involves collaborating with cross-functional teams to deliver scalable data solutions for various clients.
Marketing Operations Sênior (RevOps)
Se você tem paixão por inovação e busca trabalhar em um ambiente ágil, colaborativo e desafiador, esta pode ser a sua oportunidade! Para nosso time de RevOps , buscamos uma pessoa com forte capacidade analítica e…
Working Student Data Analytics/Engineering eMobility (f/m/d)
A working student builds and maintains data pipelines, transformations, and dashboards (Databricks/Spark, Python, SQL, Power BI) to support eMobility business use cases, including API integrations and billing workflows.
Azure Data Architect – Cloud Data & Insights Leader
Designs and builds cloud-native data systems on Azure/Databricks to transform raw data into business insights, ensuring security, scalability, and reliability.
Azure Data Architect: Cloud-Native Data Leader
Designs cloud-native data architectures on Azure to enable analytics and ML, focusing on scalable data lakes and ETL/ELT pipelines with a focus on continuous improvement (Kaizen).
AWS Data Architect: Build Scalable Data Lakes & Pipelines
Designs and builds scalable AWS data lakes and ingestion pipelines, bridging data science and engineering needs.
Azure Data Engineer: Data Science Bridge & Big Data
The Azure Data Engineer will bridge data science and engineering by managing data acquisition, transformation, and loading into data lakes for analytics and machine learning. The role involves working in a cloud-native environment using Azure services, Spark, and Databricks.
Azure Data Engineer: Bridge Data Science & Big Data
Designs and builds Azure-based data pipelines and lake loading for analytics and ML, collaborating with analysts and architects in a cloud-native environment.
Azure Data Engineer: Bridge Data Science & Cloud Analytics
Designs cloud-native data pipelines and analytics solutions using Azure/Spark tools to bridge data science and engineering teams, translating business use cases into scalable data architectures.
Azure Data Engineer
Designs and implements cloud-native data pipelines, bridges data science and engineering, and optimizes data lakes for analytics/ML using Azure tools like Databricks and Synapse.
DevOps Engineer
Builds and deploys AI/ML pipelines and data infrastructure for DHL’s global logistics operations, using cloud (Azure/GCP) and on-prem tools like Spark, Kafka, and Kubeflow to process petabytes of transactional data into predictive models and analytics.