Senior Product Manager
Analytics Platform
Posted on 10/18/2023
INACTIVE
Monitoring platform for cloud applications and services
Company Overview
Datadog stands out as a leading monitoring platform for cloud applications, offering comprehensive observability of data from various sources, which aids DevOps teams in preventing downtime and enhancing user experience. The company's culture emphasizes technical excellence and problem-solving, fostering an environment that encourages continuous learning and growth. With its unique ability to analyze and explore logs for rapid troubleshooting, Datadog holds a competitive edge in the industry, demonstrating its commitment to technical innovation and industry leadership.
Data & Analytics
Company Stage
N/A
Total Funding
$150.6M
Founded
2010
Headquarters
New York, New York
Growth & Insights
Headcount
6 month growth
↑ 5%1 year growth
↑ 17%2 year growth
↑ 88%Locations
Cambridge, MA, USA • New York, NY, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Data Analysis
Marketing
Communications
CategoriesNew
Product
Requirements
- At least 5 years of experience as a Product Manager leading the delivery of data related products in a cross functional environment
- You have strong knowledge and experience working within a data analytics ecosystem
- You have experience working with data pipelines, ETL processes/tools and Data Lakehouse
- You have hands on experience using multiple services from one or more large scale storage and/or query solutions
- You have sharp communication skills and the willingness to present your ideas to technical stakeholders and executives alike
- You have a Bachelor's Degree in Engineering, Computer Science, Information Technology, or equivalent experience
Responsibilities
- Own the end-to-end product management process for the Analytics Platform within Datadog
- Define intake, storage, query and lifecycle capabilities to support a Data Lakehouse
- Prioritize data connectors offered by the platform (ingest, query-in-place)
- Define data and machine learning models to support insights and deliver customer value
- Enable versioning, governance and compliance for data stored and served by the platform
- Define and build data transformation capabilities for internal and external customers
- Define features for customers and developers with acute focus on scale, reliability and cost
- Deliver technical marketing literature to generate awareness and drive adoption of platform features