Data Quality Engineers

Position Summary

Implement automated data quality checks, reconciliation routines, scorecards and exception monitoring for Commercial Pharma datasets. The role converts business and technical DQ requirements into scalable, reusable and production-ready validation frameworks.

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

• Build and automate DQ rules using Informatica IDMC CDQ, SQL, Databricks or equivalent frameworks.
• Develop validation checks for ingestion, transformation, reconciliation and curated data layers.
• Create DQ scorecards, exception tables, alerting logic and monitoring dashboards.
• Implement metadata-driven rule execution, thresholds, severity classification and exception routing.
• Support RCA, defect remediation, rerun validation and post-release data checks.
• Partner with DQ Analysts, Data Engineers, QA teams and Operations Manager to improve quality controls.
• 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.
  
  

• 4–7 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.
  
  

• Informatica IDMC CDQ
• SQL and Databricks validation
• DQ automation
• Reconciliation frameworks
• Exception management
• Metadata-driven checks
• Python/PySpark desirable
• Operational monitoring
  
  

• 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
  
  

• 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.
  
  

• Automated quality controls, stronger reconciliation coverage, timely exception detection and measurable DQ improvement.
  
  

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