Project description:

Design, build, and maintain scalable data platforms that transform complex, unstructured R&D data into reliable, structured, and analytics-ready assets. This role operates at the intersection of data engineering, scientific research, and digital innovation, offering a direct impact on how data is captured, structured, governed, and utilized across the client’s laboratories worldwide.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field

• ~3 years of progressive experience in data engineering, preferably in R&D, energy, chemical, or similar sectors

Proficiency:

• SQL databases

• Excel

• Python coding

• Hands-on experience with distributed data processing frameworks (e.g., Apache Spark, Databricks)

• Hands-on experience with Microsoft Azure (including Azure Blob Storage and Databricks)

Nice to have:

• Knowledge of Power Apps

• Power BI

• Web UI development skills

Tech stack:

• SQL

• Excel

• Python

• Microsoft Azure

• Azure Blob Storage

• Databricks

• Power Apps

• Power BI

Main responsibilities:

• Transform unstructured and semi-structured R&D data into standardized, governed, and analytics-ready data assets.

• Design, build, and operate scalable ETL/ELT pipelines, data lakes, and data warehouses with strong data quality, monitoring, and lineage.

• Modernize legacy data flows through APIs and integration patterns within the Microsoft Azure ecosystem (e.g., Databricks, Blob Storage).

• Optimize cloud infrastructure for performance, security, and cost efficiency while supporting enterprise data governance and compliance.

• Partner with Data Scientists, Analysts, R&D scientists, IT teams, and vendors to enable ML/AI use cases and smart laboratory initiatives.

• Identify siloed data sources and propose strategies to extract value through connectivity

• Collaborate with cross-functional teams to design, implement, and maintain web applications using the newly structured data.

• Contribute to Innovation Excellence standards, reusable components, and technical knowledge sharing across the whole company.