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Data Engineer building scalable batch and streaming pipelines, data products, and AI-facing integration layers (e.g., MCP servers) for an internal Agentic AI ecosystem using Python, SQL, dbt, orchestration tools, and cloud data platforms.
Build and maintain data pipelines and 3D geospatial tools for electricity network mapping using Python, C#, and .NET in a hybrid role.
In a few words Se anima a todos los posibles solicitantes a que se desplacen y lean la descripción completa del puesto antes de presentar su candidatura. Position: Data Engineer MLE Location: Madrid (Chamberí area).…
Location: Ghent, Belgium. ONTOFORCE helps life sciences organizations accelerate research and drug development by unlocking hidden insights from complex data. Our flagship platform, DISQOVER, is a life sciences data…
Develops and scales quantitative data products for investment teams, bridging financial domain expertise with cloud-native data engineering (BigQuery, dbt) and analytics engineering to modernize reporting, AI-ready datasets, and visualization tools like Power BI and Streamlit.
Data Science Student at Canadian Natural in Calgary, building forecasting models, ML pipelines, and interactive dashboards (Plotly Dash, Power BI) using data orchestration tools like Prefect to support DCS and control system asset reliability.
Build and maintain scalable data pipelines and ML systems for clinical trials, R&D, and drug manufacturing at a global pharma company’s applied AI team.
Builds and maintains data pipelines for ingesting, parsing, and structuring unstructured financial data (PDFs, HTML, XBRL) while integrating LLM-powered AI systems for retrieval and analytics in a FinTech context.
Designs and optimizes scalable data pipelines and AI/ML data foundations, automating ETL/ELT workflows with tools like Airflow, Databricks, and Snowflake to enable analytics and AI models across the enterprise.
Builds and maintains Vue.js-based internal tools and RFQ management systems for a Colombian organization, focusing on scalable front-end development and database integration.
Senior Data Engineer builds and refines scalable data pipelines in Python, integrates and models data from registries, and deploys solutions on Kubernetes to deliver reliable, reusable data products for government decision-making.
The Data Engineer Summer Analyst will design, build, and maintain ETL/ELT data pipelines and cloud infrastructure using Python, AWS, and Snowflake. This role involves collaborating with engineering teams to develop scalable data solutions and automate cloud configurations within an alternative asset management environment.
The Principal or Sr Principal Data Engineer will design and develop scalable ETL pipelines and data integration solutions to support enterprise analytics. The role involves architecting data ecosystems using SQL, Python, and various data warehousing technologies in a hybrid work environment.
You engineer production-grade ML systems for rail-inspection data, turning prototypes into reliable, scheduled pipelines and APIs that run on AWS and handle years of sensor data.
The ML Developer will build and scale machine learning models and data pipelines for Sber's behavioral science laboratory. The role involves fine-tuning LLMs, designing RAG architectures, and deploying production-ready AI solutions using a stack including Python, FastAPI, and various MLOps tools.
Designs and optimizes ETL pipelines, MLOps workflows, and data lakehouse architecture to power analytics and AI/ML systems for an edtech company.
Develops and scales predictive modeling platforms (embedding-based sequence encoders, survival models, gradient-boosted decision trees) to identify vulnerabilities in housing, health, and social domains using ML pipelines, containerized systems, and responsible AI practices.
The Opportunity We're looking for a Data Engineer who can translate the needs of a growing finance business into clean, reliable data systems. You'll work across a range of sources, from Bloomberg feeds to…
Lead a team to architect and build scalable data pipelines and warehouse models in Python and SQL, enabling reliable analytics and reporting for a global fertility and family care platform.
Build and maintain Mettler-Toledo’s central data platform using Databricks, Snowflake, and Python to power analytics and AI across the company.
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