Machine Learning Engineer

Capgemini Engineering; Lisboa; Híbrido; EUR 45 000 - 65 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work

Health and life insurance

Referral program

Career growth programs

Training and certifications

Resumo da oferta

Capgemini Engineering seeks a data science professional to join an agile, multidisciplinary team focused on recommendation products for residential (B2C) and SME customers. You will consolidate processes into a cross-domain framework enabling ML/AI capabilities within a lean, experimentation-driven product.

You will design and maintain scalable data pipelines using Python, PySpark and SQL, orchestrate Airflow workflows, and contribute to testing, CI/CD, and data contracts.

Qualificações

• Degree in Computer Science, Engineering, Mathematics, Statistics or another quantitative discipline.
• At least 3 years of experience building and operating production-grade data pipelines.
• Strong knowledge of Python and/or PySpark, as well as SQL.
• Experience with workflow orchestration platforms such as Airflow and CI/CD practices, ideally using GitHub.
• Good understanding of distributed computing and large-scale data processing.

Responsabilidades

• Consolidate recommendation processes across B2C and SME domains into a unified data framework.
• Design, build and maintain scalable data pipelines using Python, PySpark and SQL.
• Orchestrate workflows using Airflow DAGs deployed through Astronomer.
• Implement automated testing, deployment and CI/CD processes using GitHub.
• Ensure data quality, validation, observability and compliance with SLAs.

Conhecimentos

Python

PySpark

SQL

Data quality

Analytical skills

Communication

Problem solving

Team collaboration

Adaptability

Formação académica

Bachelor's degree in CS/Engineering/Math/Stats

Ferramentas

Airflow

GitHub

Astronomer

BigQuery/Dataproc

Descrição da oferta de emprego

CAPGEMINI ENGINEERING

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

YOUR ROLE

You will join an agile, multidisciplinary Data Science team focused on recommendation products for residential (B2C) and SME customers.

Your mission will be to consolidate existing recommendation processes into a single cross-domain framework, creating robust and scalable data foundations that enable the integration of Machine Learning and AI capabilities into a lean, experimentation-driven product.

• Consolidate recommendation processes across B2C and SME domains into a unified and scalable data framework.
• Design, build and maintain scalable data pipelines using Python, PySpark and SQL.
• Orchestrate workflows using Airflow DAGs deployed through Astronomer.
• Implement automated testing, deployment and CI/CD processes using GitHub.
• Ensure data quality, validation, observability and compliance with agreed SLAs through data contracts and testing frameworks.
• Monitor production pipelines, manage alerts, resolve incidents and automate recurring operational activities.
• Model and structure reusable data products that can be easily discovered and consumed across a data mesh environment.
• Collaborate with Data Scientists, Product Owners and business stakeholders to translate ML/AI product requirements into reliable data solutions.
• Progressively integrate ML/AI models into production environments and contribute to Data Science initiatives as the platform matures.
• Document architectures, data flows and technical decisions while contributing to the evolution of data and ML engineering best practices.

Your Profile

• Degree in Computer Science, Engineering, Mathematics, Statistics or another quantitative discipline.
• At least 3 years of experience building and operating production-grade data pipelines.
• Strong knowledge of Python and/or PySpark, as well as SQL.
• Experience with workflow orchestration platforms such as Airflow and CI/CD practices, ideally using GitHub.
• Good understanding of distributed computing and large-scale data processing.
• Strong focus on data quality and reliability, including data modelling, testing, validation and observability practices.
• Proven analytical skills, including data troubleshooting, anomaly investigation, validation of results and generation of actionable insights.
• Familiarity with Machine Learning workflows and a strong interest in evolving towards Data Science responsibilities.
• Ownership mindset with a strong focus on business impact, automation and operational excellence.
• Good communication and collaboration skills, with the ability to work effectively across technical and business teams.
• Ability to adapt and manage priorities in fast-paced and evolving environments.

Nice To Have

• Practical experience in Machine Learning, Data Science or predictive modelling.
• Experience with Google Cloud Platform (GCP), particularly BigQuery and Dataproc.
• Experience working within data mesh environments and applying data-as-a-product principles.
• Experience consolidating or harmonising processes and datasets across multiple business domains.
• Experience with Astronomer or other managed Airflow distributions.
• Experience with data quality frameworks and data contracts, such as Great Expectations or dbt tests.
• Knowledge of MLOps practices and ML/AI support pipelines, including feature engineering and model serving.

What You’ll Love About Working Here

• Join a multicultural and inclusive team environment.
• Enjoy a supportive atmosphere promoting work life balance.
• Hybrid work.
• Your career growth is central to our mission. Our array of career growth programs and diverse professionals are crafted to support you in exploring a world of opportunities.
• Access valuable training and certifications in cutting edge technologies.
• Engage in exciting national and international projects.
• Health and life insurance.
• Referral program with bonuses for talent recommendations.
• Great office locations.

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology, and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations.