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Data Engineering Lv.4

Pay
Pay not listed
Work setting
Hybrid — work setting source
Type of work model Hybrid Details to consider
Read the full posting
Employment
Not stated

What you’ll work on

Full posting
  • Build and manage ETL/ELT systems for high-volume data ingestion

  • Ensure data quality, observability, and reliability across the data lifecycle

  • Create and maintain dashboards and reporting infrastructure for PPE metrics

  • Optimize systems for performance, cost efficiency, and scalability

  • Use LLMs and prompt engineering to automate insights from unstructured data

From the employer’s posting
Build and manage analytics and production data ETL/ELT systems for high volume data ingestion from diverse sources.
Ensure data quality, observability, and reliability across the data lifecycle.
Create and maintain dashboards and reporting infrastructure to surface key PPE metrics to stakeholders.
Optimize systems for performance, cost efficiency, and scalability.
Leverage LLMs and advanced prompt engineering to automate and extract insights from unstructured data

What you’ll bring

All qualifications

Core experience

  • 3+ years of relevant working experience in a data engineering or business intelligence role.
  • Proficiency in Data modelling, SQL and Python.
  • Experience building and maintaining data pipelines (ETL/ELT) at scale.
  • Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts
  • Bachelor’s degree in Computer Science or equivalent.

Preferred experience

  • Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g.
  • Experience with distributed storage systems (e.g., HDFS, S3).
  • Familiarity with prompt engineering and using generative AI tools to solve data problems or automate content generation.
Qualification wording
3+ years of relevant working experience in a data engineering or business intelligence role.
Proficiency in Data modelling, SQL and Python.
Experience building and maintaining data pipelines (ETL/ELT) at scale.
Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts
Bachelor’s degree in Computer Science or equivalent.
Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g. Airflow, Dagster, DBT).
Experience with distributed storage systems (e.g., HDFS, S3).
Familiarity with prompt engineering and using generative AI tools to solve data problems or automate content generation.
Education & alternatives
- Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts - Bachelor’s degree in Computer Science or equivalent. Preferred Qualifications
Apply at Coupang

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 5 and day 54.

From 10,704 similar postings that came down. Coming down is not always a hire.

Coupang is hiring

39 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Power BI
  • S3
  • Tableau
  • Airflow
  • Dagster
Where the posting names them
- 3+ years of relevant working experience in a data engineering or business intelligence role. - Proficiency in Data modelling, SQL and Python. - Experience building and maintaining data pipelines (ETL/ELT) at scale.
Preferred Qualifications - Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g. Airflow, Dagster, DBT). - Experience with distributed storage systems (e.g., HDFS, S3).
- Experience building and maintaining data pipelines (ETL/ELT) at scale. - Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts - Bachelor’s degree in Computer Science or equivalent.
- Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g. Airflow, Dagster, DBT). - Experience with distributed storage systems (e.g., HDFS, S3). - Familiarity with prompt engineering and using generative AI tools to solve data problems or automate content generation.

Your next step

Complete your application on www.coupang.jobs. The employer’s form will show what is required.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

 

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.  

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. 

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.  

What You Will Do

  • Build and manage analytics and production data ETL/ELT systems for high volume data ingestion from diverse
    sources. 
  • Partner with Data Science, Engineering, and Product to enable reliable, accurate logging/implementation and usage
    across the PPE domain.
  • Ensure data quality, observability, and reliability across the data lifecycle.
  • Create and maintain dashboards and reporting infrastructure to surface key PPE metrics to stakeholders.
  • Optimize systems for performance, cost efficiency, and scalability. 
  • Leverage LLMs and advanced prompt engineering to automate and extract insights from unstructured data, and
    accelerate internal analytical workflows.
  • Define and manage SLAs for data systems.


Basic Qualifications

  • 3+ years of relevant working experience in a data engineering or business intelligence role.
  • Proficiency in Data modelling, SQL and Python.
  • Experience building and maintaining data pipelines (ETL/ELT) at scale.
  • Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts
  • Bachelor’s degree in Computer Science or equivalent.

 

Preferred Qualifications

  • Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g. Airflow,
    Dagster, DBT).
  • Experience with distributed storage systems (e.g., HDFS, S3).
  • Familiarity with prompt engineering and using generative AI tools to solve data problems or automate content
    generation.
  • Previous experience in e-commerce or retail domains.
  • Working knowledge of statistics and ML techniques.

 

Type of work model 

  • Hybrid 

 

Details to consider

  • Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

 

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Location & working pattern

Bengaluru

Type of work model - Hybrid Details to consider
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