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Full-Time

Sr. Software Engineer

Performance

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

$166k - $225kAnnually

+ Annual Performance Bonus + Equity

Senior

Mountain View, CA, USA

Category
Backend Engineering
Software Engineering
Required Skills
Databricks
Requirements
  • BS (or higher degree) in Computer Science, or a related field
  • Experience in the performance analysis discipline. Ability to identify performance issues, root cause problems, and be able to come up with potential solutions.
  • Experience in software development, preferably in large scale distributed systems
  • Ability to measure and document the impact of performance features to existing customers, such as possible regressions for certain workloads, their extent, and which customers will be affected.
  • Ability to build strong working relationships with developers and field engineers to facilitate triaging and mitigation of performance problems.
Responsibilities
  • Identify performance limitations of the entire stack based on telemetry, customer signals, PoCs, and competitive benchmarks, that will result in the best performing system across the industry, when resolved. Dimensions include latency, data and compute scalability, concurrency, cost, and price to performance ratio. Impact spans all cloud providers and all major areas.
  • Set the performance expectations for all cross-cutting efforts early on through specialized benchmarks capturing the intended customer user journeys, and make sure they are met before deployed to customers.
  • Understand the performance characteristics of the compute instance types, storage layers, and all cloud services Databricks depends on and deploy optimal solutions to meet the customer demand.
  • Work with customers to root cause and mitigate performance problems during production, previews, and POCs.

Databricks provides a unified platform that combines data lakes and data warehouses, known as lakehouse architecture, allowing organizations to manage, analyze, and gain insights from their data effectively. The platform is designed for a variety of users, including data engineers, data scientists, and business analysts, and is applicable across multiple industries such as finance, healthcare, and technology. Databricks offers features like automated ETL processes, secure data sharing, and high-performance analytics, which help streamline data management and analysis. 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 for better decision-making and insights.

Company Stage

Series I

Total Funding

$4.2B

Headquarters

San Francisco, California

Founded

2013

Growth & Insights
Headcount

6 month growth

9%

1 year growth

25%

2 year growth

80%
Simplify Jobs

Simplify's Take

What believers are saying

  • The $1 billion acquisition of Tabular is likely to enhance Databricks' data management capabilities and market reach.
  • The development and launch of the DBRX generative AI model, with a $10 million investment, underscores Databricks' dedication to leading in AI technology.
  • High-profile investments from figures like Nancy Pelosi indicate strong confidence in Databricks' growth potential.

What critics are saying

  • The integration of Tabular's team and technology could face challenges, potentially disrupting operations.
  • The competitive landscape in AI and data analytics is intense, with major players like Google and Microsoft posing significant threats.

What makes Databricks unique

  • Databricks' acquisition of Tabular, founded by the creators of Apache Iceberg, strengthens its position in the open lakehouse market.
  • The launch of DBRX, an open-source LLM that outperforms GPT-3.5 and Llama 2, showcases Databricks' commitment to cutting-edge AI innovation.
  • Strategic partnerships, such as with AVEVA for industrial AI, highlight Databricks' ability to integrate and enhance diverse technological ecosystems.

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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