Capitole Consulting keeps growing and we want to do it with you

We have an exciting opportunity for

a Data Engineer / Data Scientist

with solid experience in

data engineering, Machine Learning

and

MLOps . The role requires a

hands-on

and pragmatic professional capable of designing and implementing simple, effective and scalable data and ML solutions within tight deadlines.

Design, develop and maintain scalable

data pipelines and ETL/ELT processes .

Build and optimize data solutions using

Databricks, Python, SQL and Apache Spark .

Develop and support

Machine Learning solutions , from data preparation to model deployment.

Contribute to

MLOps processes , including model lifecycle management, deployment, monitoring and automation.

Process and analyze large datasets, ensuring

data quality, reliability and performance .

Collaborate with Data Scientists, Engineers, Analysts and business stakeholders.

Quickly translate business and technical needs into pragmatic and effective solutions.

Professional experience as a

Data Engineer, Data Scientist

or in a similar role.





Hands-on experience

with

Databricks and distributed data processing .

Strong knowledge of

Python and SQL .

Experience with

Machine Learning

and implementing ML solutions.

Knowledge and practical experience with

MLOps and model lifecycle management .

Experience building and maintaining

data pipelines and ETL/ELT processes .

Strong problem-solving skills and a pragmatic, delivery-oriented mindset.

Ability to implement effective solutions within tight deadlines.

Experience with

Apache Spark / PySpark .

Knowledge of

Azure Data Factory, Delta Lake and Azure data services .

Experience with

CI/CD

applied to Data and ML environments.

Experience with

model monitoring, deployment and performance optimization .

Previous experience in international and multicultural teams.

Languages and working model:
100% remote .

We're great, but with you we'll be even better
GFor this you

📌 Data Engineer/Scientist (Madrid)
🏢 Capitole
📍 Madrid