We seek professionals who combine strong Pharma/Lifesciences domain expertise with an AI-ready mindset, leveraging AI, GenAI, Data, and Digital Technologies to transform business processes, accelerate outcomes, and unlock new opportunities for innovation.
Roles & Responsibilites:
- Experience in handling large, complex, multi-dimensional datasets including structured, unstructured, and real time data
- Experienced in developing complex data transformation ETLs
- Strong experience in working with Python + PySpark + Apache Spark
- Strong experience of AWS cloud services related to data domain OR equivalent experience in Azure
- Strong understanding of On-Prem/Cloud Data warehouse databases
- Has technical leadership capabilities and can lead and deliver projects independently
- Understands the impact of emerging trends in data tools, analysis techniques and data usage
- Understands the concepts and principles of data modelling and can produce, maintain and update relevant data models for specific business needs
- Good to have – knowledge of cloud data engineering tools/components/technologies such as AWS Glue/EMR/Azure Data Factory, etc.
- Good to have – knowledge of Snowflake/Dataiku/Alteryx
Requirements:
- Minimum 3-5 years of data engineering experience.
- Proven experience working with Python, PySpark, Apache Spark, and data services on the cloud.
- Strong understanding of data modelling principles; ability to produce, maintain, and update data models as per specific business needs.
- Experience working with various data platforms including Snowflake/Dataiku/Alteryx.
- Knowledge of On-Prem/Cloud Data warehouse databases.
- Technical leadership skills, with a demonstrated ability to lead and deliver projects independently.
