Full-Time

Sr. Product Manager

New Initiative, Open Lakehouse

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

$109.5k - $194kAnnually

+ Annual Performance Bonus + Equity

Senior

Seattle, WA, USA

Category
Product Management
Product
Required Skills
Redshift
MySQL
Data Structures & Algorithms
Product Management
Apache Spark
Postgres
Data Analysis
Snowflake
Requirements
  • 5+ years of product management experience
  • Experience with crafting and building lucrative products with direct revenue from conception to launch
  • Proven ability to recognize customer needs, create an encapsulating product vision, translate requirements to product specifications, drive alignment with stakeholders, build and bring products to market, and drive adoption post-launch
  • Ownership and get-stuff-done attitude
  • Strong bias to ship products by understanding the most critical aspects to make the product successful
  • Bachelor's Degree in Computer Science or a related field
  • MS in Comp Science or related field or MBA
  • (Great to have) Hands-on experience with some of the data analytics products such as Apache Spark™, Postgres, MySQL, Oracle Exadata, Teradata, Netezza, Greenplum, Amazon S3, Redshift, Athena, Glue, Glacier, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS), Delta Lake, Data Lakes, Google BigQuery, Azure Synapse, Snowflake, Apache Hudi, Apache Iceberg
  • Familiarity with the basics of databases such as data structures and algorithms, row and columnar stores, networking, query optimization, and execution.
Responsibilities
  • Architect the product vision, strategy and roadmap for a cross-cutting product line, aligning with the company's goals and priorities.
  • Cultivate synergies with engineering and product leadership at major cloud service providers like Azure, AWS, GCP, to guide their roadmaps to build the best experience for our customers
  • Establish a rich ecosystem of partners to enable easy and open access to data
  • Conduct market research and user feedback to identify customer needs and pain points related to database technologies
  • Write clear and detailed product specifications, user stories and acceptance criteria for the database system technologies.
  • Partner with engineering, design, marketing and sales teams to plan, execute and launch new features and enhancements for the product line
  • Monitor and analyze the performance, usage and feedback of the database system, and use data-driven insights to inform product decisions and improvements.
  • Communicate effectively with internal and external stakeholders, including senior management, investors, partners and customers, about the value proposition, benefits and status of the product.

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 simplifies 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

$3.9B

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

  • Growing interest in generative AI models enhances Databricks' predictive capabilities and data processing.
  • Expansion of cloud-native data platforms supports scalable and resilient data architectures.
  • Increased collaboration with industry-specific partners tailors solutions for sectors like healthcare and finance.

What critics are saying

  • Increased competition from Voyage AI could threaten Databricks' market share in AI analytics.
  • Integration challenges from acquiring Tabular may impact Databricks' operational efficiency.
  • The DBRX generative AI model may not yield expected returns in a competitive market.

What makes Databricks unique

  • Databricks offers a unified platform combining data lakes and warehouses, known as lakehouse architecture.
  • The platform supports collaborative data science and machine learning workflows, enhancing team productivity.
  • Databricks integrates with various cloud services, facilitating 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