Data/ML Engineer
Role details
Job location
Tech stack
Job description
As a Data/ML Engineer, you will be part of our team in the Data & Analytics area, contributing to the design, development, and optimization of data and machine learning solutions. You will work within agile, cross-functional teams to build high-quality, scalable pipelines and ML components that support business insights and advanced analytics., * Design and develop data and ML pipelines using Python, Scala, and cloud-native tools.
- Build and maintain robust data processing workflows using Spark and SQL.
- Implement, test, and debug ML and NLP components to ensure high-quality delivery.
- Work with large, complex, and unstructured datasets to support analytical and ML initiatives.
- Collaborate with data engineers, ML engineers, data scientists, and business teams in an agile environment.
- Leverage cloud platforms and tools such as Databricks, Azure Data Factory, and Azure ML Studio.
- Contribute to continuous improvement, knowledge sharing, and best practices adoption., * Continuous training and access to official certifications.
- Work modality: Remote.
- Participation in the company's share purchase plan from day one.
- Opportunity to work on innovative projects with major clients.
- Flexible compensation plan: childcare voucher, meal voucher, transportation card, etc.
- Life and accident insurance.
- Collaborative environment and growth-oriented culture.
- Flexible career path tailored to your goals.
- Internal knowledge communities.
Here you will find a place where you can be yourself, innovate, and grow. A place where your voice matters, and your ideas become reality.
Requirements
- 2+ years of experience as a Data/ML Engineer in agile, cross-functional teams.
- Strong expertise in Python, Scala, ML, and NLP development.
- Solid knowledge of Spark, SQL, and cloud platforms.
- Familiarity with Databricks, Azure Data Factory, and Azure ML Studio.
- Skilled in testing, debugging, and handling large, unstructured datasets.
- Collaborative mindset, curiosity, and problem-solving orientation.
- Ability to work effectively in agile environments.
- Fluent English.
Nice to Have
- Degree or vocational training in Computer Science, Data Engineering, or related fields.
- Certifications or experience in cloud data ecosystems (Azure, AWS, GCP).
- Previous experience in ML Ops, model deployment, or data governance.
- Interest in continuous learning and emerging technologies.
- Familiarity with distributed computing environments., * Azure Data Factory
- English
- Python
- Scala
- Spanish
Together, as owners, let's turn meaningful insights into action.