Data Engineer
Recommended Experience: 3–6 years
Build, maintain and support data ingestion, transformation and validation pipelines for Commercial Pharma datasets. The role requires strong SQL, Python/PySpark, Databricks and Informatica IDMC skills to deliver reliable, scalable and governed commercial data assets.
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. Develop ETL/ELT pipelines using Databricks, SQL, Python/PySpark and Informatica IDMC.
Build ingestion, transformation and curated data layers for commercial pharma datasets.
Implement incremental loads, data partitioning, schema handling, error handling and recovery logic.
Support source-to-target mapping implementation, technical design, unit testing and deployment documentation.
Perform data validation, reconciliation, performance tuning and production issue resolution.
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 strong communication discipline, including status updates, risk identification,



issue escalation and timely stakeholder follow-through.
Required Work Experience

- 3–6 years of relevant experience aligned to the role and seniority level.
- Prior experience in pharmaceutical, life sciences, healthcare analytics, commercial data platforms or enterprise data programs.
- Experience working in a global delivery model with structured governance, documentation, SLAs and stakeholder communication.
- SQL and Python/PySpark

Informatica IDMC/IICS CDI
ETL/ELT design
Data warehousing
Performance tuning
Pharma commercial data awareness
Commercial Pharma Dataset Exposure
Pharmaceutical commercial data platforms
Sales, prescription, claims, CRM and omnichannel datasets
Commercial KPIs, field force effectiveness, market share and promotional effectiveness
Data quality, reconciliation, lineage, metadata and controlled release processes
Experience supporting global pharma companies or commercial data programs.
Exposure to Eisai-like commercial operating models, field reporting, sales operations and analytics use cases.
ability to explain data, risks, defects and business impact clearly.
Certifications in Databricks, Informatica IDMC, Azure/AWS, Scrum, ITIL, Tableau/Power BI or AI/ML are preferred depending on role.
Reliable pipelines, solid data accuracy, reusable code, lower defects and timely delivery of enhancements.

First 30 days: complete onboarding, understand commercial data landscape, delivery processes, documentation standards and role-specific tools.
First 90 days: demonstrate measurable ownership, improve delivery quality, identify improvement opportunities and support stable operations or project outcomes.

📌 Data Engineer - ML & AI (Secunderabad)
🏢 Axtria
📍 Secunderabad