- Own the end-to-end architecture of the modern Safety/Pharmacovigilance Data Platforms which ingests data from the several systems across clinical, non-clinical systems and transforms it into insights for internal and external users using a scalable big data pipeline on GCP.
- Design and develop flexible, scalable and resilient data processing pipelines using industry leading tools and technologies. serverless architectures, containers and Data Fabric.
- Translate business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses
- Write clear, detailed, concise documentation—architecture diagrams, reference architecture, data flows, data models, design, and implementation plan
- Partner with other teams in customer organization help them use the data platform easily and seamlessly, understand their needs and design new features and capabilities to better serve them.
- Improve our API infrastructure connecting the front-end web portals to the back-end processing engine.
- Improve our data science/ML footprint by leveraging the latest innovations in the field.
- Partner with Security and Risk Management teams to improve security posture and create and test DR plans.
- Understand the challenges of the current state, influence engineering strategy, suggest suitable new capabilities, features, and functionality.
- Should be able to write complex Scripts using Iron Python, JS, HTML, CSS along with basic functions in Python, R Scripts
- Should have through understanding of GCP services for data, analytics and AI such as BigQuery, Apache Kafka, Vertex AI, Auto ML, Gemini etc.
- Pharmacovigilance experience is must, including understanding of ArisG ecosystem for data dependency purposes
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