Senior Product Engineer

About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2024 global revenues of €22.1 billion.

Job Description:

We are looking for a highly skilled Senior Product Engineer / Developer with expertise in data engineering, pipeline development, and advanced analytics. This role involves designing and implementing scalable data solutions, building robust ETL pipelines, and developing machine learning models to drive actionable insights. The ideal candidate combines strong engineering capabilities with data science proficiency, enabling the creation of innovative, data-driven products and solutions.

Key Responsibilities

Data Engineering & Pipeline Development

• Design, implement, and optimize ETL processes to handle large-scale data ingestion and transformation tasks.
• Build scalable, high-performance data pipelines for structured and unstructured data within the EAF context.
• Ensure data quality, reliability, and security through validation, cleansing, and enrichment routines.
• Integrate cloud platforms, databases, and APIs to create efficient data architectures for advanced analytics.
• Collaborate with data scientists, analysts, and business stakeholders to ensure data is optimized for analysis and reporting.

Data Science & Analytics Development

• Develop machine learning models, algorithms, and statistical analyses to extract valuable insights from data.
• Utilize tools such as Python, R, Spark, and SQL for data processing, feature engineering, and predictive modeling.
• Analyze large datasets to identify trends, correlations, and actionable business insights.
• Build automated data pipelines for training and deploying machine learning models into production environments.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 5+ years of experience in software/product development with a focus on data engineering and analytics.
• Outstanding English communication, both verbal and non-verbal.
• Strong proficiency in Python, R, SQL, and experience with big data frameworks (e.g., Spark, Hadoop).
• Hands-on experience with ETL tools, data pipeline orchestration, and cloud platforms (AWS, Azure, GCP).
• Solid understanding of machine learning techniques, statistical modeling, and data visualization.
• Familiarity with API integration, microservices, and containerization (Docker, Kubernetes).
• Excellent problem-solving skills and ability to work in Agile/DevOps environments.