5 publicaciones de empleo destacadas de ai full stack en madrid, md (¡Están contratando!)

Senior Data Platform / Data Engineer
Straumann Group —Madrid, Madrid provincia
- Jornada completa
- AWS
- Machine learning
- Python
Client Manager
Lenovo —Madrid, Madrid provincia
- Ventas
- Inglés
- Grado
Revenue Programs Manager
Make —Madrid, Madrid provincia
- Ventas
- Salesforce
- Inglés
- Seguro de vida
Revenue Enablement Manager (m/f/d)
Speexx —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- CRM software
- Ventas
- Inglés
Solicitud rápida
Senior Product Marketing Manager (f/m/d)
Apaleo —Madrid, Madrid provincia
- Teletrabajo
- Inglés
- Marketing
- Vacaciones pagadas
Solicitud rápida
7d

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Senior Data Platform / Data Engineer

Straumann Group -
Madrid, Madrid provincia

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Detalles del empleo

Jornada completa

Cualificaciones

CI/CD
AWS
Machine learning
PostgreSQL
Python

Descripción completa del empleo

Straumann Group
At Straumann Group we’re on an exciting journey of growth, innovation, and impact - driven by our mission to improve oral health and transform millions of lives worldwide. United by purpose, we bring our best selves to work every day, embracing a high-performance, player-learner culture that inspires collaboration, curiosity, and ambition. Here, you’ll have the opportunity to take charge of your own career, harnessing your skills, passion, and enthusiasm for learning to continually grow and progress. Together, we’re not just shaping brighter smiles, we’re unlocking the potential of people everywhere, including our own.

About the role
We are looking for a Senior Data Platform / Data Engineer to join our ML Platform team and help build and scale the data infrastructure that powers our AI products in dentistry. Our platform supports the full AI development lifecycle, from raw data ingestion and annotation workflows to dataset versioning and model training pipelines. You will work closely with Machine Learning Researchers (MLRs), MLOps engineers, and product teams to ensure our data infrastructure is reliable, scalable, and easy to use.
A key focus of the role is improving our Data Lakehouse (DLH) and dataset management workflows, including dataset versioning (DVC) and improving how data is prepared, extracted, and consumed across research and production systems.

What you will work on:
You will play a key role in shaping the next generation of our data platform.
Typical responsibilities include:
Data platform ownership

Design and evolve the Data Lakehouse (DLH) architecture used across our ML teams.
Improve the reliability and structure of data ingestion, extraction, and transformation pipelines.
Ensure datasets used for training and evaluation are consistent, reproducible, and well documented.

Dataset lifecycle management

Improve workflows for dataset versioning and reproducibility using tools such as DVC.
Design solutions for managing multiple versions of datasets and annotations across experiments and models.
Improve the ability for researchers to retrieve the correct dataset versions reliably.

Data pipelines and infrastructure

Build and maintain scalable data pipelines in Python.
Improve metadata management, dataset validation, and data quality monitoring.
Optimize data workflows across AWS-based infrastructure.

Collaboration with ML teams

Work closely with ML researchers and ML engineers to understand their data needs.
Support research workflows with reliable and efficient data access patterns.
Help translate research requirements into robust platform capabilities.

Data governance and quality

Implement practices for data quality, reproducibility, and traceability across the ML lifecycle.
Ensure our data infrastructure meets the requirements of regulated AI development.

What we’re looking for:
Must have:

Strong Python engineering skills
Experience building data pipelines or data platforms
Experience working with AWS
Experience working with large datasets used in ML workflows
Strong software engineering practices (testing, CI/CD, documentation)
Experience collaborating with ML teams or working in AI environments

Nice to have:

Experience with dataset versioning tools such as DVC
Experience with Kubernetes
Experience with data lakehouse architectures
Experience working with annotation pipelines or ML training datasets
Experience with PostgreSQL, Metabase, or similar data tooling
Experience working in regulated environments (medical / healthcare AI)

Our stack

AWS
Python
Kubernetes
PostgreSQL
Metabase
DVC for dataset versioning
Internal Data Lakehouse infrastructure

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.

Employment Type: Full Time

Alternative Locations: Spain : Madrid || Poland : Gdansk || Poland : Warsaw || Poland : Wroclaw

Travel Percentage: 0 - 10%

Requisition ID: 20071

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