Data Engineer with Life Sciences domain experience

Data Engineer from Life sciences domain 

Role responsibilities:

• Build automated computational pipelines for in vitro data capture, processing, quality control, and ingestion into centralized databases.
• Develop scalable data visualization dashboards and reporting tools to enable routine analysis, experiment review, and crossstudy comparisons.
• Contribute to the development and integration of AIenabled tools, including earlystage AI agent workflows, to enhance data accessibility and scientific productivity.
• Collaborate with biologists, data scientists, and informatics partners to understand data needs and deliver robust, analysisready solutions.
• Communicate project progress, challenges, and deliverables proactively with the manager and key stakeholder

• MS or BS in Computer Science, Data Engineering, Bioinformatics, Data Science, or a related field.
• 2-4 years (MS) or 4- 6 years (BS) post-graduate working experience in biotech/pharma industry.
• Strong experience developing data pipelines and analytical workflows using Python and/or R.
• Demonstrated experience building interactive data visualization dashboards or reporting tools.
• Experience working with backend databases and exposure to machine learning operations (MLOps) concepts