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Spotify
Spotify

Music for everyone.

Data Analyst II – Performance Optimization Squad

직무데이터 분석
경력미들급
위치Stockholm
근무오피스 출근
고용정규직
게시3주 전
지원하기

The Performance Optimization Squad is a newly formed team in the Core Infrastructure Studio with a mission to establish a core competency in performance engineering and address systemic inefficiencies across Spotify's platform. With 3,200+ microservices, 40,000 VMs at peak, and 500,000 K8s pods, even minor fleet-wide efficiency improvements result in substantial cost savings. We've already identified $8M+ in annual savings from our first initiative alone, and we're just getting started. This squad works horizontally across the entire stack — but none of that optimization happens without the data to see it. We're looking for a Data Analyst who will build the measurement foundation that drives every decision we make.

전체 조회수

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전체 지원 클릭

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전체 Mock Apply

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전체 스크랩

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Spotify 소개

Spotify

Spotify

Public

Spotify is a Swedish audio streaming and media service provider founded in April 2006 by Daniel Ek and Martin Lorentzon. As of December 2025, it was one of the largest providers of music streaming services, with over 751 million monthly active users comprising 290 million paying subscribers.

5,001-10,000

직원 수

Stockholm

본사 위치

$23B

기업 가치

리뷰

10개 리뷰

4.1

10개 리뷰

워라밸

3.8

보상

4.2

문화

4.5

커리어

4.0

경영진

2.8

75%

지인 추천률

장점

Flexible working hours and remote options

Great team culture and supportive colleagues

Creative freedom and innovative projects

단점

High workload and stress during peak times

Fast-paced environment can be overwhelming

Management disorganization and direction issues

연봉 정보

20개 데이터

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Associate Data Scientist

0개 리포트

$142,458

총 연봉

기본급

-

주식

-

보너스

-

$121,089

$163,827

면접 후기

후기 4개

난이도

3.0

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 75%

부정 25%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit