Position Summary

Bridge data engineering and AI engineering for Commercial Pharma datasets. The role builds AI-ready data pipelines, embedding pipelines, vector stores, feature-ready datasets and metadata integrations needed to power GenAI, semantic search and agentic analytics use cases.

Business / Program Context

The role is part of a Vizag-based delivery capability supporting Commercial Pharma datasets across global markets. The work may include platform operations, data engineering, data quality, reporting, AI enablement, release governance and stakeholder support for enterprise commercial data products. The role is not limited to Japan-specific datasets; Japan market familiarity may be useful but is not a mandatory baseline requirement for most positions.

Job Responsibilities

Prepare AI-ready commercial datasets using Databricks, SQL, Python and PySpark.
Build embedding pipelines, vector database ingestion and semantic search indexes.
Create metadata, lineage, chunking, retrieval and refresh processes for enterprise knowledge sources.
Support RAG solution development,



evaluation datasets and AI application integration.
Implement data quality, access control, monitoring and refresh logic for AI pipelines.
Work with AI Engineers, Data Engineers, Platform Engineers and governance teams to productionize AI use cases.
Work as part of a Vizag-based delivery team supporting Commercial Pharma datasets and global commercial data stakeholders.
Collaborate with business, technology, governance, quality and offshore/onshore delivery teams across time zones.
Follow Agile delivery, SDLC, documentation, release, validation, access-control and data-governance standards.
Contribute to knowledge management, reusable assets, SOPs, runbooks and operational excellence initiatives.
Maintain solid communication discipline, including status updates, risk identification, issue escalation and timely stakeholder follow-through.

Required Work Experience

3–7 years of relevant exper

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