Senior Data Engineer @ Entalpic

**Senior Data Engineer**: **Our company: Entalpic**: We are a dedicated team at the forefront of AI and chemistry, working to accelerate the energy transition. Our focus is on discovering new chemicals and materials that can lead to more sustainable practices in sectors where the need for change is most urgent. Specifically, we develop a modern generative AI platform to discover new catalysts that optimize chemical reactions, significantly reducing CO2 emissions and thus making a substantial impact on the environment. As an early-stage AI-driven startup backed by significant funding (>5m), we base our approach on state-of-the-art academic research to drive practical business solutions. We value clear communication and simplicity in our approaches, promoting a constant optimization mindset. Join Entalpic to be part of a growing team, eager to learn and adapt, united by the belief that our technology can make a significant positive impact and contribute to transforming carbon-intensive industries for a sustainable future. Co-founders: Mathieu Galtier, Victor Schmidt, Alexandre Duval Entalpic is dedicated to equal opportunity employment and fosters an environment that is open and respectful of diversity. All applicants are encouraged to apply, even if you don’t meet all above requirements. If you have passion for our mission and believe you can contribute, we want to hear from you. **Reporting & Job Location**: You will report to the **CTO** of Entalpic and will be located in our **Paris** offices. **Mission Highlights**: As a centerpiece member of Entalpic’s team, you will undertake two core missions: - ** - ** Data Platform Enhancement**: lead to the development of our internal data platform, facilitating efficient data access and interaction (including through AI agents), and promoting a data-centric culture within the organization. **Role & responsibilities**: - ** Data Engineering**: Build and optimize scalable data pipelines to process and integrate multimodal data from simulations (e.g., DFT outputs), textual sources (e.g., research papers, patents) and experimental data (e.g. time series or imagery from acquisition hardware). - ** Data Storage Solutions**: Implement and manage robust data storage systems, ensuring data integrity, accessibility, and scalability to support various analytical and machine learning tasks. - ** Automation and Scripting**: Develop scripts and tools to automate data ingestion, processing, and transformation tasks, enhancing workflow efficiency and reducing manual intervention. - ** Data Governance and Lineage**: Establish and enforce data governance policies, ensuring proper data lineage tracking, quality control, and compliance with relevant data protection standards. - ** Infrastructure Support**: Collaborate with DevOps and infrastructure teams to ensure that data engineering solutions are well-integrated into the overall system architecture, leveraging cloud platforms like AWS or GCP for deployment and scalability. - ** Collaboration and Support**: Work closely with cross-functional teams, including data scientists and domain experts, to understand data requirements and provide tailored solutions that facilitate data-driven decision-making. - ** Open Source Engagement**: Contribute to open-source projects and initiatives, sharing knowledge and tools developed internally to foster community engagement and collaboration. **Profile**: - ** M.S** in Computer Science, Computer Science, Data Engineering, or a related field. - ** 7+ years of experience** in data engineering, with a proven track record of handling diverse data modalities and building scalable data infrastructures. - Proficiency in at least **two programming languages** (e.g., Python, Scala, Rust, Go, etc.) and experience with _both_ SQL (MySQL & PostgreSQL) and NoSQL (MongoDB) databases. - Strong understanding of data modeling, ETL processes, and data warehousing solutions. - Experience with cloud platforms, particularly AWS or GCP, and familiarity with infrastructure-as-code tools. - Excellent communication skills in English, with the ability to work collaboratively in interdisciplinary teams. - Thrives in a fast-paced, evolving startup environment. - Bonuses:_ - Experience with machine learning pipelines and deploying AI training infrastructures. - Contributions to open-source projects and active participation in relevant communities. - Familiarity with scientific data processing and analysis, particularly in the context of materials science. **Expertise**: - ** Programming**: Strong software engineering skills in Python and at least one other programming language, with experience in software development best practices and version control systems such as Git. - ** Data Management**: In-depth knowledge of data structures and database systems, both SQL and NoSQL, to manage and process large datasets efficiently. - ** Cloud Platforms**: Experience with cloud services (AWS, GCP) and infrastructure-as-co