Data Engineers

Data Engineer

Job Location: Vizag, India

Recommended Experience: 36 years

Position Summary

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.

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

• 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 with DQ Analysts/Engineers to implement business and technical validation rules.
• Support release cycles, code reviews, defect fixes and operational enhancements.
• 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

• 36 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.
• Ability to work from Vizag and collaborate effectively with India, global and client teams.

Technical / Functional Skills

• SQL and Python/PySpark
• Databricks Delta Lake
• Informatica IDMC/IICS CDI
• ETL/ELT design
• Data warehousing
• Performance tuning
• Git and CI/CD basics
• Pharma commercial data awareness

Commercial Pharma Dataset Exposure

• Pharmaceutical commercial data platforms
• Sales, prescription, claims, CRM and omnichannel datasets
• Customer master, HCP/HCO, product master, territory and alignment datasets
• Commercial KPIs, field force effectiveness, market share and promotional effectiveness
• Data quality, reconciliation, lineage, metadata and controlled release processes

Desirable Skills

• Experience supporting global pharma companies or commercial data programs.
• Exposure to Eisai-like commercial operating models, field reporting, sales operations and analytics use cases.
• Japan market dataset exposure is preferred but not mandatory unless the assignment requires direct Japan business engagement.
• Strong written and verbal communication skills; 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.

Success Measures / KPIs

• Reliable pipelines, strong data accuracy, reusable code, lower defects and timely delivery of enhancements.

Indicative 30 / 60 / 90 Day Expectations

1. First 30 days: complete onboarding, understand commercial data landscape, delivery processes, documentation standards and role-specific tools.
2. First 60 days: independently contribute to assigned workstreams, support issue resolution, produce required artifacts and participate in governance forums.
3. First 90 days: demonstrate measurable ownership, improve delivery quality, identify improvement opportunities and support stable operations or project outcomes.