
Building the Future of Data Infrastructure
6 days ago
We are seeking a Data Engineer with strong analytical and technical expertise to drive our data-driven transformation. You will be responsible for building and maintaining data infrastructure and pipelines, enabling robust analytics and machine learning initiatives across multiple departments.
This role requires hands-on experience with data engineering tools and platforms, a solid foundation in Python and SQL, and ideally some domain knowledge in chemical processes or related industries. You will work closely with stakeholders in R&D and regulatory teams to enable data accessibility, insight generation, and technical innovation.
- Assemble large, complex datasets that meet functional and non-functional business requirements.
- Design and implement internal process improvements, including infrastructure re-architecture for scalability, optimized data delivery, and automation of manual workflows.
- Build infrastructure for efficient data extraction, transformation, and loading (ETL) using AWS and SQL technologies.
- Develop and maintain automated data pipelines across sources like SQL Server, LIMS, Veeva, and unstructured text files.
- Create analytical tools and dashboards (e.g., Power BI reports, RAG systems) to drive key insights on operational efficiency and customer acquisition.
- Prototype solutions for innovation teams using integrated datasets, including ML and generative AI applications.
- Support stakeholders with data infrastructure needs and resolve data-related technical issues.
- Lead technical projects and coordinate with external vendors/ consultants to deliver robust data solutions.
- Act as a liaison between internal subject matter experts and technical partners to ensure effective knowledge transfer.
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