Data & AI Engineer

• Design and implement scalable data lake architectures using Amazon S3
• Build and optimize serverless analytics solutions with Amazon Athena
• Define efficient data models, partitioning strategies, and metadata management
• Develop robust ETL / ELT pipelines using AWS Glue, Lambda, and Step Functions
• Ingest structured and semi-structured data from internal systems, APIs, and external sources
• Ensure data quality, validation, and schema evolution across pipelines
• Implement data governance with AWS Lake Formation and IAM
• Manage encryption, access control, and auditability for sensitive datasets
• Monitor and optimize performance and cloud costs using CloudWatch and AWS cost tools
• Enable self-service data access for analytics, BI, and data science teams
• Support downstream use cases: dashboards, analytics platforms, and ML workloads
• Contribute to documentation, standards, and best practices
• Design, train, and evaluate NLP and LLM-based solutions, including: Retrieval-Augmented Generation (RAG)
• Chatbots and information retrieval
• Text generation, summarization, and information extraction
• Prepare and curate data for training, fine-tuning, and evaluation
• Build and manage AI agents and workflows using tools such as AWS Bedrock, LangGraph, or similar
• Stay up to date with generative AI innovations and apply them in real-world solutions

• 4+ years of experience in data engineering or cloud data platforms
• Strong hands-on experience with Amazon S3 and Amazon Athena
• Excellent SQL skills for analytical querying and optimization
• Solid experience with AWS services: Glue, Lambda, IAM, CloudWatch
• Experience provisioning cloud infrastructure and setting up CI/CD pipelines (GitHub Actions)
• Strong knowledge of data formats (Parquet, ORC, JSON, CSV)
• Programming experience in Python, PySpark, or similar
• Experience designing and operating data lakes or analytics platforms
• Good understanding of data lifecycle management
• Familiarity with BI tools and analytics consumption patterns
• Hands-on experience with LLMs and generative AI in a professional environment
• Knowledge of deep learning and data science libraries (NumPy, Pandas, TensorFlow, PyTorch)
• Collaboration mindset
• Comfortable working in cross-functional and international teams
• Strong collaboration with platform, frontend, and AI engineers
• Ability to translate business needs into data-driven solutions

Experience in healthcare or clinical data environments is a strong plus

• An international community bringing together more than 110 different nationalities
• An environment where trust is central: 70% of our leaders started their careers at the entry level
• A strong training system with our internal Academy and more than 250 modules available
• A dynamic work environment that frequently comes together for internal events (afterworks, team buildings, etc.)