Senior Data Engineers

Job description

Sr. Data Engineer **Job Location:** Vizag, India **Recommended Experience:**710 years **Position Summary** Lead complex engineering design and delivery for Commercial Pharma datasets from Vizag. The role provides technical leadership across Databricks, Informatica IDMC, data modeling, performance tuning, code quality, architecture alignment and engineering best practices. **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** - Translate solution designs into scalable and maintainable data engineering patterns. - Lead complex Databricks and IDMC pipeline design, optimization and delivery. - Review code, technical designs, mappings, unit test evidence and deployment plans. - Mentor Data Engineers and establish coding standards, reusable frameworks and performance guidelines. - Resolve complex data, performance, orchestration, dependency and production issues. - Partner with architects, platform teams, DQ teams, QA teams and business analysts to ensure end-to-end delivery quality. - Drive engineering improvements such as metadata-driven ingestion, automation and reusable validation frameworks. - 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** - 710 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** - Advanced Databricks engineering - Advanced SQL/PySpark - Informatica IDMC/IICS - Data modeling and Delta optimization - Technical leadership - Code review and mentoring - Cloud data architecture - Operational troubleshooting **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** - High-quality technical delivery, reduced rework, better performance, stronger engineering discipline and effective mentoring. **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.