Timescale

Senior/Staff Product Manager, Platform

Remote

Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Database Software, Cloud Computing, SaaSIndustries

Position Overview

  • Location Type: Remote
  • Job Type: Full-Time
  • Salary: (Salary information not provided)

Timescale is a product-led growth organization empowering businesses with real-time insights. They are building a modern PostgreSQL cloud platform and are looking for an experienced Sr/Staff Product Manager to lead key customer-facing features of their cloud platform, including horizontal scaling, high availability, and a new storage engine. This role offers an opportunity to build the next great cloud-native database for developers worldwide.

Requirements

  • Experience leading highly technical platform products end-to-end.
  • Deep understanding of customers and their problems.
  • Ability to identify jobs to be done and build product strategies.
  • Strong collaboration skills with design and engineering teams.
  • English language fluency is required.
  • Preferred candidate should work during East Coast American or European time zones.

Responsibilities

  • Develop a deep understanding of customers, the competitive landscape, and market trends.
  • Identify problems to focus on and define the steps to solve them.
  • Provide engineering and design with necessary customer, market, and business context.
  • Articulate the value of new products and features before building them.
  • Define pricing and packaging strategies in collaboration with finance.
  • Collaborate with product marketing, marketing, and sales to define positioning and messaging.
  • Define and measure success for new features and capabilities.

Application Instructions

  • (Application instructions not provided)

Company Information

  • Timescale is a mostly remote company with a globally diverse, remote-first team.
  • They are focused on building a modern PostgreSQL cloud platform.
  • They aim to empower businesses with real-time insights from their data.

Skills

Platform product management
Customer insights
Product strategy
Cross-functional collaboration
Market analysis
Pricing strategy
Positioning and messaging
Success metrics definition

Timescale

Time series data management and analytics

About Timescale

Timescale specializes in managing time series data through its main product, TimescaleDB, which is an open-source database designed to efficiently handle large volumes of data points collected over time. Built on PostgreSQL, TimescaleDB offers reliable performance and operational efficiency. The company serves various industries, including IoT and financial services, enabling clients to analyze and gain insights from time series data for improved decision-making and automation. Timescale differentiates itself by providing both on-premise and cloud-based solutions, along with a freemium model that allows users to access the core product for free while offering premium features and enterprise support for revenue. The goal of Timescale is to enhance how businesses manage and analyze time series data, making it easier and more effective for organizations to leverage their data.

New York City, New YorkHeadquarters
2015Year Founded
$179.8MTotal Funding
SERIES_CCompany Stage
Data & Analytics, Enterprise SoftwareIndustries
51-200Employees

Risks

Increased competition from Neon offering serverless Postgres databases.
Rebranding as a cloud company may confuse existing customers, risking churn.
Growing popularity of serverless platforms challenges Timescale's traditional offerings.

Differentiation

TimescaleDB is built on PostgreSQL, ensuring reliability and operational efficiency.
Offers both on-premise and cloud-based solutions, catering to diverse business needs.
Freemium model with open-source core attracts a large user base.

Upsides

Increased adoption of edge computing aligns with Timescale's time-series database offerings.
Rise of serverless computing creates opportunities for scalable, on-demand resources.
Growing trend of digital twins boosts demand for robust time-series data management.

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