Product Manager - Skylar Analytics

Role Overview

Skylar Analytics is ScienceLogic's data and reporting layer — the product that takes operational telemetry from across a customer's Skylar One deployments and other enterprise data sources and makes it accessible, unified, and intelligent.

This role sits at the intersection of data access and reporting product. You'll own the data access layer — defining the structures, connectors, and reporting templates that make it easy for customers to get value from their operational data out of the box, whether through Superset, Power BI, or their own BI tooling.

Responsibilities

• Own the Skylar Analytics product vision and roadmap, spanning data modeling requirements, customer-facing reporting, and query capabilities.
• Own the data access layer by defining and delivering connectors, data structures, and Power BI and Superset reporting templates that customers can use directly, reducing time-to-value without custom development.
• Collaborate with data engineering and data science teams to define and continually refine the operational data model, ensuring it reflects customer needs and remains extensible.
• Partner with the Skylar One team to define and maintain the data pipeline contract, including which operational data is sent to the Skylar AI platform, at what fidelity, and how it evolves as both products grow.
• Drive anomaly detection and predictive alerting in Analytics by defining which ML outputs customers see and how they use them.
• Partner with the Skylar Advisor team to strengthen shared data infrastructure and identify ways to feed Analytics data into Advisor’s agentic capabilities.
• Own the GTM strategy for Skylar Analytics, including positioning, packaging, and the narrative that establishes Analytics as a compelling standalone product.

Skills

• 5+ years of experience as a Product Manager for a reporting, analytics, or BI product, with a track record of shipping dashboards and reporting templates that non-technical users can easily use.
• Comfort collaborating with data engineers on data modeling concepts, including dimensional modeling, OLAP cubes, schema design, and query performance tradeoffs.
• Hands-on SQL experience, with the ability to write queries, inspect data directly, and validate assumptions without relying on an analyst.
• Familiarity with the modern data stack, including ClickHouse, dbt, data warehouse architecture, and the design and maintenance of analytical pipelines.
• Familiarity with BI tools such as Superset, Power BI, Tableau, or similar platforms, and how enterprise teams use them for operational reporting.
• Sufficient fluency in data science concepts to collaborate effectively on anomaly detection and ML pipelines, including knowing which questions to ask without a requirement to build models.
• Experience leading GTM for a technical product, with the ability to partner with sales and marketing to translate data platform capabilities into clear customer value.
• Experience with multi-tenant SaaS products and the operational complexity they introduce.
• Experience with using Jira software.

Nice to Have

• Background in IT operations, observability, or infrastructure monitoring.
• Experience with agentic AI products or LLM-powered platforms.
• Familiarity with Open Telemetry or metrics ingestion pipelines.
• Experience with data governance and cataloging, including making data discoverable and trustworthy for customers who are not data engineers.
• Experience with Apache Superset.
• Experience with ClickHouse database.