Machine Learning Engineer

Capgemini

Lisboa

Presencial

EUR 48 165 - 65 679

Tempo integral

14 dias+

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Vantagens oferecidas por esta oferta de emprego

Hybrid work
Health and life insurance
Referral program

Resumo da oferta

Capgemini Engineering in Lisbon looks for a Machine Learning Engineer to consolidate holistic data foundations for ML products. You will design and operate scalable data pipelines with Python, PySpark and SQL, and orchestrate workflows using Airflow deployed through modern CI/CD practices.

Collaboration with data scientists and stakeholders is essential to evolve ML-ready data solutions. The role emphasizes data quality, observability, and governance, with opportunities to contribute across data

Qualificações

  • Degree in Computer Science, Engineering, Mathematics or a quantitative field.
  • 3+ years building and operating production-grade data pipelines.
  • Strong Python, PySpark and SQL knowledge with data-focused mindset.
  • Experience with Airflow and CI/CD, ideally GitHub-based workflows.
  • Familiarity with distributed computing and large-scale data processing.

Responsabilidades

  • Consolidate B2C and SME recommendation data into a unified data framework.
  • Design, build and maintain scalable data pipelines using Python, PySpark and SQL.
  • Orchestrate workflows with Airflow DAGs and deploy via CI/CD processes.
  • Ensure data quality, validation and observability with data contracts and tests.
  • Monitor pipelines, manage incidents and automate recurring tasks.
  • Collaborate with Data Scientists and Product Owners to translate ML/AI needs into data solutions.
  • Document architectures and data flows; evolve data and ML engineering practices.

Conhecimentos

Python
PySpark
SQL
Airflow
CI/CD
GitHub
Data quality
Observability
Data modeling
ML workflows

Formação académica

Bachelor's degree in Computer Science or related

Ferramentas

Airflow
GitHub
BigQuery
Dataproc
dbt
Great Expectations

Descrição da oferta de emprego

# Machine Learning EngineerLisboaApply for this job* Permanent* Experienced Professionals* Data & AI* ID 522129-en\_GB## CAPGEMINI ENGINEERINGAt 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 ROLEYou 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.You will:* 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.
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