Position: Data Engineer MLE
INSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and experience in scientific research, development, manufacturing, sales, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health.

The activities of INSUD PHARMA are organized into three synergistic business areas: Industrial (Chemo), Branded (Exeltis), and Biotech (mAbxience), with over 9,000 professionals in more than 50 countries, 20 state-of-the-art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. INSUD PHARMA believes in innovation and sustainable development.

AI Engineers, Data Scientists, DevOps Engineers, Product Managers building the systems that power how trials get designed, how patients get recruited, and how everything gets monitored once the trial is live.

Clinical trials run on data. We are seeking a highly skilled Data Engineer / Machine Learning Engineer to join our Applied AI Team. The ideal candidate combines strong software engineering foundations with hands-on experience in data pipelines and machine learning systems, and enjoys working at the intersection between data, models, and production systems.

As a Data Engineer / MLE at AI Labs, you will work closely with data scientists, software engineers, and product owners to design, build, deploy, and operate end-to-end data and machine learning solutions across multiple business units — including Regulatory, Clinical Trials, R&D, Pharmacovigilance, and Drug Manufacturing.

This role is critical to ensuring that AI models move reliably from experimentation to production, supported by scalable data pipelines, robust ML infrastructure, and strong engineering standards.

You will work alongside Data Scientists, AI Engineers, DevOps Engineers, and Product Managers who are equally committed to delivering high-quality work.
The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city.

Design, build, and maintain scalable data pipelines for data ingestion, transformation, and serving, supporting both analytics and machine learning use cases.
Develop and productionize machine learning pipelines , covering training, validation, deployment, and monitoring.
Collaborate closely with Data Scientists to translate notebooks and prototypes into robust, production-ready ML systems .
Implement model deployment patterns (batch, real-time, or hybrid) using APIs, scheduled jobs, or event-driven architectures.
Build and maintain feature pipelines and data abstractions that enable reproducible and reliable model behavior.
Ensure data quality, versioning, and traceability across datasets and models.
Optimize pipelines and ML workloads for performance, scalability, and cost efficiency.
Work with DevOps and Platform teams to deploy solutions using containerization and CI/CD best practices.
Contribute to defining data engineering and MLOps standards across AI Labs. Proficient in Spanish and English , written and verbal communication.
Strong proficiency in Python , including clean code practices, packaging, and modular design.
Solid understanding of software engineering principles (OOP, SOLID, testing, version control).
Hands-on experience building data pipelines (ETL / ELT) using Python-based frameworks or custom solutions.
Experience working with machine learning workflows , including model training, evaluation, and deployment.
Familiarity with REST APIs and service-based architectures (FastAPI, Flask, or similar).
Experience with containerization (Docker) and cloud environments (AWS or Azure).
Experience with MLOps practices (model versioning, monitoring, drift detection, retraining strategies).
Familiarity with orchestration tools (e.g., Airflow, Prefect, Dagster).
Experience with data storage systems (SQL / NoSQL databases, data lakes, object storage).
Familiarity with ML frameworks and scientific libraries (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
Flexible start time from Monday to Friday
Permanent contract.
Training and language learning platform
♀️ We will continue with an in-person/virtual interview depending on availability and what we agree upon; there may be one or two interviews in the process, and depending on the type of process, there may also be some kind of test.
➡️ Follow us on social media like LinkedIn/Instagram and stay tuned for any offers we may release; The InsudPharma group is aware that business management must align with the needs and demands of society, and therefore assumes the commitment to equal opportunities and treatment between men and women, as stated in the current regulations on the matter - Organic Law 3/2007, and we do not discriminate against any person on the grounds of ethnicity, religion, age, sex, nationality, marital status, affective or sexual orientation, gender identity or expression, disability, or any other personal or social circumstance.

AWS Data Engineer, hibrido

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AWS Data Engineer, hibrido

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