Senior Data Analyst

Position Description

The Senior Data Analyst is hands-on analytics professional based in Pune, working in close daily collaboration with U.S.-based business, data, and analytics leadership. This is a delivery-focused role, accountable for producing trusted, decision-ready insights and analysis that support operational and strategic decision-making across the enterprise.

This role owns the end-to-end execution of analytics—from shaping business questions into analytical approaches, through data validation, analysis, visualization, and insight communication—ensuring metrics are consistent, credible, and aligned to enterprise definitions. Insights produced in this role are expected to directly inform business decisions, recommendations, and prioritize discussions with stakeholders.

This role requires strong quantitative aptitude and a high level of comfort working extensively with numbers, data sets, and analytical problem-solving, including applying statistical reasoning to business questions (interpreting trends, distributions, and variability).

Work Location & Schedule Expectations

This role is based in Pune and works in close daily collaboration with U.S.-based engineering leadership and cross-functional teams.

• Work Model: Hybrid, TBD days per week in the office, coordinated with the team to ensure consistent shared in-person working days.
• U.S. Collaboration: Daily schedule must include 3 to 4 hours of overlap with U.S. Eastern Time (ET) to support active collaboration with U.S.-based business, data, and analytics team.
• Operational Availability: This role may require availability during critical reporting cycles, business reviews, or production data issues, which may occasionally fall outside standard working hours.

Qualifications & Experience

Required Experience

• Bachelor’s degree in Analytics, Statistics, Mathematics, Computer Science, Engineering, Business, or a related field, or equivalent practical experience.
• Total years of experience 6–10, with relevant business intelligence and analytics experience minimum of 5 years.
• Demonstrated experience operating as a senior individual contributor, independently owning analytical problem framing, analysis, execution, and insight delivery.
• Demonstrated experience delivering production analytics, dashboards, and reporting in an enterprise environment.
• Advanced SQL proficiency, including complex joins, subqueries/CTEs, and window functions; ability to work effectively with large enterprise datasets.
• Hands-on experience with BI and visualization tools (e.g., Power BI, Tableau, Looker, Domo, Qliksense or other complementary tools) and semantic models.
• Data modeling competency for analytics/semantic layers (e.g., star schema, fact/dimension concepts) to support consistent and performant reporting.
• DAX (or equivalent) proficiency to build enterprise measures, KPIs, and time-intelligence logic, or complementary calculation skills across BI stacks (e.g., Tableau calculated fields/LOD, LookML measures, MDX for OLAP, and SQL-based semantic/metric layers).
• Experience validating data, identifying data quality issues, and partnering with data engineering teams on resolution.
• Experience supporting analytics across domains such as sales, customers, products, and business units.
• Familiarity with statistical and experimentation fundamentals, including hypothesis testing and basic A/B testing concepts.

Preferred Experience

• Experience using Python (or R) for data analysis, statistical analysis, or exploratory analysis.
• Familiarity with Power Query (or equivalent) for data shaping and transformation in BI workflows.
• Familiarity with cloud-based data warehouses or analytics platforms (e.g., Snowflake, BigQuery, Redshift, Azure Synapse).
• Experience optimizing BI models and calculations for usability and performance.

Key Duties and Responsibilities

Analytics Delivery & Insight Generation

• Partner with business stakeholders to clarify objectives, success criteria, and decision context prior to analysis.
• Translate business questions into structured analytical approaches that clearly connect insights to decisions.
• Perform trend, variance, and root-cause analysis to identify performance drivers, risks, and opportunities.

Reporting, Dashboards & Metrics

• Design, build, and maintain dashboards, scorecards, and KPI reporting that are intuitive, accurate, and action oriented.
• Define and maintain KPI logic and measures within the semantic layer to ensure consistent metric outcomes across reports.
• Ensure metrics are standardized, clearly defined, and aligned to enterprise definitions.
• Continuously refine reporting to improve clarity, usability, and relevance for stakeholders.
• Ensure analytical outputs are based on accurate, complete, and trusted data.
• Identify data quality issues in upstream sources and collaborate with data engineering teams on remediation.
• Work with semantic models, master data, and governed datasets to maintain consistency across reports.