Full-Time

Sr. Engineering Manager

Spark Platform

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

$222k - $300kAnnually

+ Annual Performance Bonus + Equity

Senior

Mountain View, CA, USA

Category
Engineering Management
Software Development Management
Required Skills
Product Management
Apache Spark
Databricks
Data Analysis
Requirements
  • 5+ years experience working in a related system, including ecosystem, Apache Spark and database internal, database systems, data processing or related domains.
  • A passion for database systems, distributed systems, API design, or performance optimization.
  • Can ensure the team builds high-quality and reliable infrastructure services. Experience being responsible for testing, quality, and SLAs of a product; previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals.
  • Ability to attract, hire, and coach engineers who meet the Databricks hiring standards. Can uplevel existing teams via hiring top-notch senior talent, growing leaders, and helping struggling members. Can gain trust of the team and guide their careers; experience managing distributed teams preferred.
  • Comfort working cross-functionality with product management and directly with customers; ability to deeply understand product and customer personas.
Responsibilities
  • Lead a high-performing engineering team in the development of the Spark platform, reinforcing the Apache Spark™ position as the world’s leading open-source unified engine for large-scale data analytics.
  • Lead and participate in technical, product, and design discussions focused on database systems and Apache Spark™.
  • Define, shape, and drive the future of both Apache Spark™ and the Databricks Data Intelligence Platform.
  • Oversee the recruitment of top-tier talent to build a cohesive and dynamic engineering team.
  • Foster leadership within the team through coaching, mentorship, and providing growth opportunities.
  • Implement strategic processes to efficiently realize the product vision, strategy, and roadmap.
  • Collaborate with internal and external stakeholders to ensure alignment with organizational goals.
  • Evolve the organizational structure to support long-term initiatives and build strong teams with effective communication.

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. The company operates on a subscription-based model, generating revenue from platform access and professional services. The goal of Databricks is to empower organizations to leverage their data effectively for better decision-making.

Company Stage

Growth Equity (Venture Capital)

Total Funding

$3.9B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

6%

1 year growth

35%

2 year growth

74%
Simplify Jobs

Simplify's Take

What believers are saying

  • Growing demand for data lakehouse solutions boosts Databricks' market potential.
  • Acquisition of Tabular aligns with the trend towards open-source data management tools.
  • Expansion in AI and machine learning applications benefits Databricks' key sectors.

What critics are saying

  • Increased competition from Voyage AI challenges Databricks' market position in AI analytics.
  • Integration of Tabular may pose challenges and distract from core operations.
  • Significant investment in DBRX model could impact finances if returns are not met.

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 various 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