Full-Time

Sr. Engineering Manager

Release and Deployment Infrastructure

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

San Francisco, CA, USA

Category
Engineering Management
Software Development Management
Required Skills
Kubernetes
Microsoft Azure
Airflow
Docker
AWS
Jenkins
Terraform
Google Cloud Platform

You match the following Databricks's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • BS (or higher) in Computer Science, or a related field
  • 5+ years of experience building and leading a team of engineers working in a related system
  • Passion for building highly scalable and reliable infrastructure
  • Experience with cloud APIs and technologies e.g. a public cloud such as AWS, Azure, and/or GCP
  • Experience with build, release and deployment infrastructure technologies such as Spinnaker, Jenkins, Airflow, Docker, Kubernetes, Terraform, Bazel, etc.
  • 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 up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members; can gain trust of the team and guide their careers
  • Comfort working on cross-functional projects with the ability to deeply understand product and customer personas
Responsibilities
  • Build and lead a talented engineering team that develops critical infrastructure needed to build and deploy our Databricks Runtime releases in a controlled and efficient manner
  • Partner with our development teams to improve efficiency of release life cycle development activities
  • Lead our release team by overseeing Databricks Runtime Releases to ensure high quality delivery of our standard, machine learning and Photon runtimes
  • Oversee sustained recruitment of top-tier talent, fostering a well-organized and synergistic team structure, and collaborating effectively with internal and external stakeholders
  • Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities

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. Databricks aims to simplify data management and analytics for its users.

Company Stage

Debt Financing

Total Funding

$13.6B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

0%

1 year growth

1%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Databricks raised $15 billion for AI product development and global expansion.
  • The acquisition of BladeBridge enhances Databricks' capabilities in automated data migration.
  • Increased demand for real-time analytics boosts adoption of Databricks' platform.

What critics are saying

  • Increased competition from Snowflake challenges Databricks' lakehouse architecture.
  • Integration challenges from BladeBridge acquisition may disrupt workflows and delay rollouts.
  • Reliance on large-scale debt financing poses financial risks if market conditions change.

What makes Databricks unique

  • Databricks' lakehouse architecture combines data lakes and warehouses for efficient data management.
  • The platform supports collaborative data science and machine learning workflows, enhancing team productivity.
  • Databricks integrates seamlessly with various cloud services, supporting multi-cloud strategies.

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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