Product Owner

Overview

Technical Product Owner focused on product analytics and telemetry, serving as the single source of truth for product performance, user adoption, and platform utilization.

What you'll do

• Query, blend, and analyze data across Databricks Delta Lake, Snowflake, PostgreSQL, WalkMe, and Datadog to quantify real-world impact of Jira initiatives.
• Architect and maintain Databricks SQL dashboards and visualizations tracking cohort adoption, funnel drop-offs, feature utilization, and user retention.
• Map downstream user telemetry back to Jira initiatives and epics, measuring feature rollout velocity against actual adoption metrics.
• Synthesize analytical outputs into executive-level presentations that highlight adoption bottlenecks, quantify platform usage, and drive prioritization.
• Partner with engineering and data platform teams to define event taxonomies, tracking specifications, and governance standards.
• Conduct cohort and behavioral analyses to discover user behavior, navigation friction, and platform optimization opportunities.

What you'll need

• 3–6+ years of hands-on experience in Senior Product Analyst, Product Analytics, or Analytics Engineering within a modern SaaS/cloud environment.
• Advanced SQL, including window functions, recursive CTEs, query optimization, and handling semi-structured JSON payloads, across PostgreSQL, Databricks, and Snowflake.
• Practical experience pulling or stitching disparate product data from application logs, clickstream tools, guidance software (WalkMe), and cloud storage (e.g., Azure Blob, S3).
• Strong familiarity working natively within the Databricks ecosystem (Databricks SQL, Lakeview dashboards, Delta tables).
• Solid understanding of modern product management frameworks, Jira project/initiative hierarchies, and KPI definitions (DAU/MAU, activation rates, cohort retention).
• Exceptional ability to build clean, persuasive decks and clearly present technical findings to non-technical leadership.

Nice to have

• Educational or applied background in Data Science, Computer Science, Statistics, or Analytics Engineering.
• Working knowledge of PySpark, Python for data manipulation, or dbt.
• Experience operating within cloud ecosystems (Azure or AWS) and understanding Delta Lake architecture.
• Experience defining user event tracking frameworks from scratch (e.g., event naming conventions, schema contracts).

Details

• Location: Hyderabad, India.