Product Data Analyst

Role - Product Data Analyst Experience - 5+ Years Mode of interview - 1st round Face-To-Face Hyderabad, Hybrid Model Required Qualifications 5–7 years of professional experience in a product analytics, business analytics, or data analyst role supporting digital products, eCommerce, or B2B platforms. • Demonstrated ability to build, ship, and maintain production-quality dashboards and reports in at least one of: DOMO, Google Looker (LookML), or Power BI with working familiarity across more than one preferred. • Hands-on experience working in DOMO and Snowflake data environments, including writing strong, performant SQL against large data sets. • Track record of independently turning ambiguous business questions into structured analyses and clear, actionable insights you can dig into the data without being told exactly where to look. • Excellent written and verbal communication skills, with the ability to translate technical findings for non-technical audiences and senior leaders. • Demonstrated experience prioritizing across multiple stakeholders, negotiating scope and timelines, and managing your own workload to deliver consistently. Preferred Qualifications Experience supporting product teams in a manufacturing, industrial, or technical eCommerce environment ideally with exposure to digital quoting, configurator-driven workflows, or custom-manufactured goods (e.g., CNC, injection molding, 3D printing, sheet metal). • Familiarity with web and product analytics tooling (e.g., Google Analytics 4, Adobe Analytics, Amplitude, Mixpanel, Heap) and event-level data. • Working knowledge of statistical concepts, A/B testing, and experimentation frameworks. • Comfort with Python or R for deeper, ad-hoc analysis beyond SQL. • Experience contributing to data modeling work (e.g., dbt, semantic layers, LookML) in partnership with a central Data & Analytics team. Reporting & Visualization • Design, build, and maintain dashboards and self-service reports in DOMO, Google Looker, or Power BI to give product managers and stakeholders a reliable, real-time view of the business. • Define, document, and govern key product and eCommerce metrics so the organization speaks a common language about performance. • Continuously improve existing reports sunsetting what is no longer used, consolidating overlap, and ensuring what remains is accurate, performant, and easy to understand. Data Engineering Partnership • Work fluently across our DOMO and Snowflake data environments writing performant SQL, validating data quality, and understanding the lineage behind the metrics you publish. • Partner with the Data & Analytics team to define data requirements, refine data models, and advocate for the upstream changes needed to support reliable product analytics. • Help establish and follow standards for analytical work documentation, version control, naming conventions, and reproducibility. • Understand and navigate highly independent datasets, with the ability to assess schema differences, metric definitions, and join logic to avoid misalignment, double-counting, or misleading outputs. • Validate joins, aggregations, and filters through spot checks, reconciliation against known benchmarks, and peer review before insights or charts are shared with stakeholders.