About the Job :

We are building a high-fidelity chemical intelligence platform.

This role is for engineers at the early stage of their careers who want to work on real, production-grade data platforms where scientific correctness, provenance, and reproducibility matter.

The problems you'll work on :

- Structuring unstructured global chemistry literature into machine-reasonable data

- Supporting systems that fuse public chemical knowledge with proprietary experimental data

- Contributing to a molecule- and reaction-centric knowledge graph

- Helping maintain accurate and evolving master data for chemicals

Responsibilities :

- As a Data Platform Engineer, you will work on the foundational data infrastructure that empowers our R&D with AI/ML, Robotics, Analytics and Reporting use cases

- Contribute to building and operating data pipelines that ingest patents, journals, and scientific datasets

- Help transform noisy, semi-structured scientific literature into structured, high-fidelity, and provenance-aware data

- Work with senior engineers to support a molecule- and reaction-centric knowledge graph platform

- Add data quality checks, logging, and monitoring to ensure correctness

Minimum qualifications :

- Bachelor's degree in Computer Science or related discipline from a tier-1 institution

Strong fundamentals in :

- Data structures and algorithms

- Databases and SQL

- Operating Systems and Networking

- Basic distributed systems concepts

- Familiarity with at least one programming language such as Python, Java, Go, or Scala

- Exposure to data processing concepts (ETL/ELT, batch processing, basic streaming)

- Ability to reason clearly about problems and explain design choices

- Strong inclination towards learning domain knowledge and complex systems

Preferred qualifications :

- Internship, academic, or project experience building data pipelines or backend systems

- Exposure to distributed data processing frameworks (e.g., Spark or Flink)

- Basic familiarity with data lakes, warehouses, or NoSQL databases

- Interest in scientific, technical, or research-heavy domains