Full-Time

Sr. Product Manager

Data Management

Confirmed live in the last 24 hours

Databricks

Databricks

5,001-10,000 employees

Unified data platform for analytics and AI

Data & Analytics
Enterprise Software
AI & Machine Learning

Compensation Overview

$115.4k - $204.2kAnnually

+ Annual Performance Bonus + Equity

Senior

San Francisco, CA, USA

Category
Data Management
Product Management
Product
Data & Analytics
Required Skills
Product Management
Data Analysis
Requirements
  • 5+ years of product management and related experience with enterprise or SaaS products.
  • Educational or professional background in computer science or related engineering fields.
  • Ability to partner with senior technical leaders from Engineering, while going deep on technical concepts.
  • Track record of delivering products with cross-functional teams common to enterprise software industry (field engineering, sales, marketing, partnerships, etc.)
  • Analytical skills to make data-driven decisions (e.g. analyze product usage)
  • Excellent communication skills to clearly and concisely communicate complex topics to diverse stakeholders (engineers, customers, etc.) in written and verbal form.
  • A background in Data Warehousing is a plus but not required.
Responsibilities
  • Product management for a new and emerging business at Databricks
  • Make company wide impact by driving across the Databricks product portfolio
  • Own the full life cycle of product development from ideation to requirements, development, pricing, launch, and go-to-market.

Databricks provides a platform that combines the features of data lakes and data warehouses, referred to as lakehouse architecture. This platform allows organizations to efficiently manage, analyze, and gain insights from their data. It caters to a diverse clientele, including data engineers, data scientists, and business analysts in sectors like finance, healthcare, and technology. Databricks streamlines data ingestion, management, and analysis through automated ETL processes, secure data sharing, and high-performance analytics. Additionally, it supports machine learning and AI workloads, enabling users to build and deploy models at scale. Unlike many competitors, Databricks operates on a subscription-based model, generating revenue through platform access and professional services. The company's goal is to empower organizations to leverage their data effectively for better decision-making and insights.

Company Stage

Growth Equity (Venture Capital)

Total Funding

$13.6B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

9%

1 year growth

38%

2 year growth

79%
Simplify Jobs

Simplify's Take

What believers are saying

  • Databricks raised $10 billion for AI product development and global expansion.
  • The company plans to expand into Saudi Arabia, aligning with Vision 2030.
  • Partnerships with cloud providers enhance Databricks' scalability and performance.

What critics are saying

  • Increased competition from Snowflake could impact Databricks' market share.
  • The acquisition of Tabular may pose integration challenges and disrupt operations.
  • Rapid expansion into new markets may expose Databricks to geopolitical risks.

What makes Databricks unique

  • Databricks offers a unified platform combining data lakes and warehouses, known as lakehouse.
  • The platform supports collaborative data science and machine learning workflows.
  • Databricks integrates with major cloud services for seamless data management and analysis.

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Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave