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Match Group
Seoul, South Korea (Hybrid)

Data Infra Platform Team Leader

4 Months ago โ€ข All levels

Job Summary

Job Description

13 skills required

Job Details

[Platform Department ์†Œ๊ฐœ]

Hyperconnect Platform Department๋Š” Data Infra Platform, Data Product Dev, SRE, DevOps, Core Platform, IT ๋“ฑ ๊ตฌ์„ฑ์›๋“ค์ด ๋ชจ์—ฌ ์ค‘์•™ ํ”Œ๋žซํผ๊ณผ ์‹œ์Šคํ…œ ์ธํ”„๋ผ ๊ฐœ๋ฐœ ์šด์˜ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. Azar, ์‹ ๊ทœ ํ”„๋กœ๋•ํŠธ, AI/ML, Media ๋“ฑ ์ „์‚ฌ ๋ชจ๋“  ์„œ๋น„์Šค์— ์ธํ”„๋ผ์™€ ๊ณตํ†ต ํ”Œ๋žซํผ ๊ธฐ์ˆ ์„ ์ œ๊ณตํ•˜๊ณ  ์œ ๊ด€๋ถ€์„œ์™€ ์ ๊ทน์  ํ˜‘์—…์„ ํ†ตํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์˜์—ญ์—์„œ ๋น„์ฆˆ๋‹ˆ์Šค ์ž„ํŒฉํŠธ๋ฅผ ๋งŒ๋“ค์–ด๋‚ด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ „์‚ฌ ๊ธฐ์ˆ  ์กฐ์ง์˜ Siloํ™”๋ฅผ ๋ฐฉ์ง€ํ•˜๊ณ  ํšจ์œจ์ ์ด๊ณ , ์ƒ์‚ฐ์„ฑ์ด ๋›ฐ์–ด๋‚œ ์—”์ง€๋‹ˆ์–ด๋ง ๋ฌธํ™”๋ฅผ ๋งŒ๋“ค์–ด๊ฐ€๋Š”๋ฐ ์ง‘์ค‘ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.



[Data Infra Platform Team ์†Œ๊ฐœ]

- Data Infra Platform ํŒ€์€ Data Engineer๋“ค์ด ๋ชจ์—ฌ, ์ „์‚ฌ ์ง์› ๋ชจ๋‘๊ฐ€ ์‚ฌ์šฉํ•˜๋Š” Data Infra Platform์„ ํšจ์œจ์ ์ด๊ณ , ์‚ฌ์šฉํ•˜๊ธฐ ํŽธ๋ฆฌํ•˜๊ฒŒ ๋งŒ๋“ค๊ธฐ ์œ„ํ•œ ์—”์ง€๋‹ˆ์–ด๋ง ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ํŒ€์ž…๋‹ˆ๋‹ค.
- Data ์ธํ”„๋ผ๋“ค์„ ์ฝ”๋“œ ๊ธฐ๋ฐ˜์œผ๋กœ ์ฒด๊ณ„์ ์œผ๋กœ ๊ด€๋ฆฌํ•ฉ๋‹ˆ๋‹ค.
- ๋‹ค์–‘ํ•œ Modern Data Platform์— ํ•„์š”ํ•œ ๋„๊ตฌ, SaaS ๋“ฑ์„ ์—ฐ๊ตฌํ•˜๊ณ  Production์— ๋„์ž…ํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ์ด๊ฒƒ๋“ค์„ ์ „์‚ฌ ์ง์›์ด ์‰ฝ๊ฒŒ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ˜•ํƒœ๋กœ ๋„๊ตฌ๋‚˜ ๊ด€ํ–‰์„ ์—ฐ๊ตฌํ•˜๊ณ  ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค.
- Data ๋ชจ๋ธ, ํŒŒ์ดํ”„๋ผ์ธ์„ ๊ฐœ๋ฐœํ•˜๊ธฐ ์œ„ํ•œ CI/CD ํ™˜๊ฒฝ์„ ๊ตฌ์ถ•ํ•˜๊ณ  ๊ด€๋ฆฌํ•ฉ๋‹ˆ๋‹ค.
- External/In-House ์‹œ์Šคํ…œ์˜ Data Ingestion์„ ์ผ๊ด€๋˜๊ณ  ๋ณ€ํ™”๊ด€๋ฆฌ์— ์œ ์—ฐํ•œ ํ˜•ํƒœ๋กœ ์šด์˜ ๋  ์ˆ˜ ์žˆ๋„๋ก ์—ฐ๊ตฌํ•˜๊ณ , ์ˆ˜์ง‘ ํ€„๋ฆฌํ‹ฐ ๊ด€๋ฆฌ๋ฅผ ๋‹ด๋‹นํ•ฉ๋‹ˆ๋‹ค.
- ๋ฐ์ดํ„ฐ ๊ฒ€์ฆ ๋ฐ ์šด์˜์„ ์œ„ํ•œ ๋„๊ตฌ๋ฅผ ๊ฐœ๋ฐœํ•˜๊ณ  ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.
- DataOps ๊ด€ํ–‰์„ ์—ฐ๊ตฌํ•˜๊ณ  ๋„์ž…ํ•ฉ๋‹ˆ๋‹ค.



[Data Infra Platform Team์— joinํ•˜์‹ ๋‹ค๋ฉด]

- Data Mesh, Self Service Data Platform ์„ ์‹คํ˜„ํ•˜๊ธฐ ์œ„ํ•ด, ์ฃผ๋„์ ์œผ๋กœ Ideation์„ ํ•˜๊ณ  ์ง์ ‘ ๊ฑฐ๋ฒ„๋„Œ์Šค ๋ฐ ์‹œ์Šคํ…œ์„ ๋””์ž์ธ ํ•ด๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
- ๋ฉ€ํ‹ฐ ํ”„๋กœ๋•ํŠธ ๊ธฐ๋ฐ˜์˜ ๋‹ค์–‘ํ•œ ๋„๋ฉ”์ธ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์ฃผ๋„์ ์œผ๋กœ ๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
- ๋ฐ์ดํ„ฐ ํŒŒ์ดํ”„๋ผ์ธ ์œ ์ง€ ๊ด€๋ฆฌ๋ฅผ ๋›ฐ์–ด๋„˜์–ด, ๋ฐ์ดํ„ฐ ๊ธฐ๋ฐ˜์œผ๋กœ ๋น„์ฆˆ๋‹ˆ์Šค ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์‹œ์Šคํ…œ ๊ตฌ์ถ• ๋ฐ ๋””์ž์ธ์„ ํ•ด๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
- ๋น„์ฆˆ๋‹ˆ์Šค์— ํ•„์š”ํ•œ Data Application์„ ๊ฐœ๋ฐœํ•ด ๋ณผ ์ˆ˜ ์žˆ๋Š” ๊ฒฝํ—˜์„ ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
- ๊ธ€๋กœ๋ฒŒ ๋ฐ์ดํ„ฐ๋ฅผ ๋‹ค๋ฃจ๋‹ค ๋ณด๋‹ˆ ๊ทœ๋ชจ๊ฐ€ ๊ต‰์žฅํžˆ ํฌ๊ณ  (์ˆ˜์‹ญ TB/day ์ด์ƒ), ๋Œ€๋Ÿ‰์˜ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๊ธฐ์ˆ ์ ์œผ๋กœ ๋‹ค์–‘ํ•œ ๊ณ ๋ฏผ๊ณผ ์‹œ๋„๋ฅผ ํ•ด๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
- ๊ธฐ์กด ๋ณด๋‹ค ๋‚˜์€ ๋ฐฉํ–ฅ์„ ๋Š์ž„์—†์ด ์—ฐ๊ตฌํ•˜๊ณ , ํ•ฉ๋ฆฌ์ ์œผ๋กœ ์ƒˆ๋กœ์šด ์—…๋ฌด ์ฒด๊ณ„๋‚˜ ์‹œ์Šคํ…œ ๋„์ž…์„ Production์— ์ ์šฉ ํ•ด๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
- EKS, Bigquery, Databricks, Airflow๋ฅผ ํ™œ์šฉ ์ค‘์ด๋ฉฐ, ํผ๋ธ”๋ฆญ ํด๋ผ์šฐ๋“œ๊ธฐ๋ฐ˜์˜ ๋‹ค์–‘ํ•œ ๋ฐ์ดํ„ฐ ์ธํ”„๋ผ ๋ฐ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๊ฒฝํ—˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Responsibilities

    • ๋ฐ์ดํ„ฐ Ingestion ์ž๋™ํ™” ํŒŒ์ดํ”„๋ผ์ธ ์‹œ์Šคํ…œ ๊ตฌ์ถ• ๊ด€๋ฆฌ
    • Data Lakehouse ๊ตฌ์ถ• ๊ด€๋ฆฌ ๋ฐ ์ž๋™ํ™”
    • Data Platform ์‚ฌ์šฉ ๊ฐ€์ด๋“œ ์ž‘์„ฑ ๋ฐ ์ „ํŒŒ
    • ๋ฐ์ดํ„ฐ ์นดํƒˆ๋กœ๊ทธ, ๋ฆฌ๋‹ˆ์ง€ ์ถ”์  ์‹œ์Šคํ…œ ๊ตฌ์ถ• ๋ฐ ๊ด€๋ฆฌ
    • Data Infra ๋น„์šฉ ์ตœ์ ํ™”
    • ML์กฐ์ง๊ณผ ML ํ•™์Šต ํŒŒ์ดํ”„๋ผ์ธ ์ตœ์ ํ™” ์ž‘์—… ์ง€์›
    • ์ „์‚ฌ DataOps Lifecycle์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋น„ํšจ์œจ์ ์ธ ์—…๋ฌด๋ฅผ ์ •์˜ํ•˜๊ณ  Automation ์—…๋ฌด๋ฅผ ์ˆ˜ํ–‰
    • Market์—์„œ ๋Š์ž„์—†์ด ์ถœ์‹œํ•˜๋Š” ๋‹ค์–‘ํ•œ Data Infra Platform ๋„๊ตฌ๋“ค๊ณผ ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ ๋ฐ PoC

Required Qualifications

    • 5๋…„ ์ด์ƒ์˜ ๋ฐ์ดํ„ฐ ์—”์ง€๋‹ˆ์–ด๋ง ์‹ค๋ฌด ๊ฒฝํ—˜
    • RDBMS, NoSQL์— ๋Œ€ํ•œ ๊ธฐ๋ณธ์ ์ธ ์ดํ•ด๊ฐ€ ์žˆ์œผ์‹ ๋ถ„
    • SQL์„ ์‚ฌ์šฉํ•˜์—ฌ ์ž์‹ ์ด ๋ถ„์„ํ•˜๊ณ ์ž ํ•˜๋Š” ๊ฒƒ์„ ๋Šฅ์ˆ™ํ•˜๊ฒŒ ๊ตฌํ˜„ ๊ฐ€๋Šฅํ•˜์‹  ๋ถ„
    • Python์„ ๋Šฅ์ˆ™ํ•˜๊ฒŒ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์œผ์‹œ๊ณ , ํ•„์š”ํ•œ ๊ฒฝ์šฐ API ์„œ๋ฒ„๋“ฑ์„ ํ™œ์šฉํ•ด ์ž๋™ํ™” ๋ฐ In-House ์‹œ์Šคํ…œ์„ ๋นŒ๋“œํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐœ๋ฐœ ๋Šฅ๋ ฅ์„ ๋ณด์œ ํ•˜์‹  ๋ถ„
    • Tableau, Power BI, Looker ๋˜๋Š” ์ด์™€ ์œ ์‚ฌํ•œ BI ๋„๊ตฌ ์‚ฌ์šฉ ๊ฒฝํ—˜์ด ์žˆ์œผ์‹  ๋ถ„
    • Git/Git Actions ์‚ฌ์šฉ์— ๋Šฅ์ˆ™ํ•˜์‹  ๋ถ„
    • Databricks, Spark ๋“ฑ์„ ํ™œ์šฉํ•œ ์‹ ๋ขฐ์„ฑ ์žˆ๋Š” ๋Œ€๊ทœ๋ชจ ๋ฐ์ดํ„ฐ ํŒŒ์ดํ”„๋ผ์ธ ๊ตฌํ˜„์ด ๊ฐ€๋Šฅํ•˜์‹  ๋ถ„
    • ๋‹ค์–‘ํ•œ ํ˜•ํƒœ์˜ ๋ฐ์ดํ„ฐ ๋กœ๊ทธ๋“ค์„ ๋‹ค๋ฃจ์–ด ๋ณธ์ ์ด ์žˆ๊ณ , ํ‘œ์ค€ ๋ฐ์ดํ„ฐ๋กœ๊ทธ ์„ค๊ณ„์™€ ๋ณ€ํ™”๊ด€๋ฆฌ ์„ค๊ณ„๋ฅผ ํ•ด๋ณด์‹  ๋ถ„
    • Airflow(ETL)์— ๋Šฅ์ˆ™ํ•˜๊ณ  ํŠธ๋Ÿฌ๋ธ” ์ŠˆํŒ…์„ ์ฃผ๋„์ ์œผ๋กœ ํ•ด๊ฒฐํ•ด ๋ณด์‹  ๋ถ„
    • ์˜์–ด๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ๋ฏธํŒ…๊ณผ ๋ฉ”์ผ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜์ด ๊ฐ€๋Šฅํ•˜์‹  ๋ถ„
    • AWS, Google Cloud๋“ฑ ํผ๋ธ”๋ฆญ ํด๋ผ์šฐ๋“œ ํ”Œ๋žซํผ์— ๋Œ€ํ•ด ์‚ฌ์šฉ ๊ฒฝํ—˜์ด ์žˆ์œผ์‹  ๋ถ„
    • Terraform ๋“ฑ IaC ๋„๊ตฌ๋ฅผ ํ†ตํ•ด ๋ฐ์ดํ„ฐ ์ธํ”„๋ผ ๊ด€๋ฆฌ๋ฅผ ์ˆ˜ํ–‰ํ•ด๋ณด์‹  ๋ถ„
    • ์ „์‚ฌ์˜ ๋‹ค์–‘ํ•œ ์ดํ•ด๊ด€๊ณ„์ž๋“ค๊ณผ ํ˜‘์—…ํ•˜๊ณ  ๋ณต์žกํ•œ ์—”์ง€๋‹ˆ์–ด๋ง ๋ฌธ์ œ๋ฅผ ์ดํ•ดํ•˜๊ธฐ ์‰ฝ๊ฒŒ ์ „๋‹ฌํ•  ์ˆ˜ ์žˆ๋Š” ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜ ๋Šฅ๋ ฅ์„ ๊ฐ–์ถ”์‹ ๋ถ„
ํ•˜์ดํผ์ปค๋„ฅํŠธ๊ฐ€ ์ฑ„์šฉํ•˜๋Š” ํฌ์ง€์…˜์— ์ง€์›ํ•˜๋Š” ๊ฒฝ์šฐ, ๊ฐœ์ธ์ •๋ณด ์ฒ˜๋ฆฌ์— ๊ด€ํ•˜์—ฌ์„œ๋Š” ๋ณธ ๊ฐœ์ธ์ •๋ณด์ฒ˜๋ฆฌ๋ฐฉ์นจ์ด ์ ์šฉ๋ฉ๋‹ˆ๋‹ค: https://career.hyperconnect.com/privacy

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About The Company

Sr. Machine Learning Engineer (MG AI)

Seoul, South Korea (On-Site)

Machine Learning Engineer (MG AI)

Seoul, South Korea (On-Site)

Senior QA Analyst

New York, New York, United States (On-Site)

Product Operations Specialist

Palo Alto, California, United States (Hybrid)

Product Operations Specialist

Los Angeles, California, United States (Hybrid)

Product Operations Specialist

San Francisco, California, United States (Hybrid)

Staff Product Manager, Machine Learning and Recommendations

San Francisco, California, United States (Hybrid)

Staff UX Researcher

San Francisco, California, United States (Hybrid)

Staff UX Researcher

Los Angeles, California, United States (Hybrid)

Product Design Manager, Design Systems and Accessibility

Palo Alto, California, United States (Hybrid)

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