Senior Data Analyst - Pharma or Life Sciences

As a Senior Data Analyst in the Pharma or Life Sciences domain located in Gurugram with 5 to 10 years of experience, your main responsibilities will include: - Designing, developing, and maintaining dashboards and reports using tools such as Databricks SQL, AI/BI Dashboard, and Power BI for regulatory, clinical, and supply chain use cases. - Translating business requirements into KPI definitions, metrics frameworks, and reporting specifications with clear drill-down paths, filters, and user personas. - Building and optimizing analytical datasets and reporting views on top of Gold and Published layer tables in the Databricks Lakehouse. - Conducting trend analysis, variance analysis, and root-cause analysis to support business performance monitoring and decision-making. - Profiling source data to assess quality, completeness, and fitness for reporting. Identifying data gaps and working with data engineers to resolve them. - Creating and maintaining data dictionaries, business glossaries, and source-to-report lineage documentation. - Developing self-service analytics capabilities enabling business users to access governed data and build their own views with minimal dependency on the analytics team. - Automating recurring reports to reduce manual effort and improve consistency across stakeholder groups. - Partnering with business stakeholders to gather reporting requirements, present findings, and iterate on dashboard designs based on feedback. - Supporting UAT and validation of reporting outputs, ensuring accuracy against source data and business rules. - Participating in Agile ceremonies: backlog grooming, sprint planning, sprint reviews, and stakeholder demos. Qualifications required for this role include: - 6 years of experience in data analytics, BI reporting, or dashboard development role. - Life sciences or pharma domain experience is required. - Exposure to G&A, regulatory operations, clinical data, or supply chain analytics is strongly preferred. - Hands-on proficiency in SQL for data analysis, profiling, transformation, and validation. - Experience building dashboards and reports using at least one of: Power BI, Tableau, Databricks SQL Dashboard, Looker, or Qlik. - Understanding of data modeling concepts: star schemas, dimensional models, fact/dimension tables, and how reporting layers connect to underlying data pipelines. - Experience defining KPIs, metrics frameworks, and reporting specifications aligned with business objectives. - Ability to work with curated data in a cloud data warehouse or lakehouse environment (Databricks, Snowflake, BigQuery, or similar). - Strong analytical and problem-solving skills. Comfortable working with large datasets and translating findings into business recommendations. - Hands-on experience with Jira and Confluence. - Strong understanding of Agile/Scrum methodologies. - Must be ready to overlap with PST business hours. - Proficiency in Microsoft Excel (pivot tables, VLOOKUP, advanced formulas) for ad-hoc analysis. Additionally, the following qualifications are considered "Good to Have": - Experience with Databricks SQL, AI/BI Dashboard, or Genie for self-service analytics. - Familiarity with Veeva RIM, Veeva Vault, or Veeva CRM data and reporting requirements. - Experience with clinical data reporting (CSRs, biostats, medical publications) or regulatory submission tracking dashboards. - Understanding of pharma supply chain reporting: inventory, procurement, distribution, demand projections. - Exposure to Python or PySpark for data analysis and automation. - Experience with data quality profiling and validation as part of the reporting workflow. - Understanding of PHI/HIPAA compliance requirements in data and reporting environments. As a Senior Data Analyst in the Pharma or Life Sciences domain located in Gurugram with 5 to 10 years of experience, your main responsibilities will include: - Designing, developing, and maintaining dashboards and reports using tools such as Databricks SQL, AI/BI Dashboard, and Power BI for regulatory, clinical, and supply chain use cases. - Translating business requirements into KPI definitions, metrics frameworks, and reporting specifications with clear drill-down paths, filters, and user personas. - Building and optimizing analytical datasets and reporting views on top of Gold and Published layer tables in the Databricks Lakehouse. - Conducting trend analysis, variance analysis, and root-cause analysis to support business performance monitoring and decision-making. - Profiling source data to assess quality, completeness, and fitness for reporting. Identifying data gaps and working with data engineers to resolve them. - Creating and maintaining data dictionaries, business glossaries, and source-to-report lineage documentation. - Developing self-service analytics capabilities enabling business users to access governed data and build their own views with minimal dependency on the analytics team. - Automating recurring reports to reduc