Data Platform Engineer

Astro Indonesia; Jakarta Barat; On-site; IDR 350,000,000 - 700,000,000; Full time

Job summary

Astro Indonesia is seeking a Data Platform Engineer — External Data Acquisition to build and operate platforms for acquiring data from external sources, including websites, apps, APIs, and public datasets. You will own the acquisition layer from extraction to landing data for downstream processing.

The role focuses on production-grade data acquisition for pricing and market intelligence, collaborating with Pricing, Data Warehouse Engineering, and Data Analysts to turn external-data needs into

Qualifications

• Strong Python/software engineering fundamentals.
• Hands-on experience building or operating web scraping, crawling, external API, or similar data acquisition systems.
• Strong understanding of HTTP, APIs, JSON, headers, cookies, sessions, authentication, pagination, and request/response behavior.
• Hands-on experience with browser/network debugging and the ability to investigate how websites or applications communicate with their backend services.
• Experience with browser automation tools such as Selenium, Playwright, Scrapy, or equivalent.
• Understanding of retry, timeout, rate limiting, concurrency, idempotency, and failure recovery.
• Solid understanding of SQL, data storage/warehousing, schema evolution, workflow orchestration, and cloud infrastructure.
• Strong troubleshooting skills for external systems outside control.

Responsibilities

• Build and maintain reliable web/app crawlers, scrapers, and external API integrations across e-commerce, marketplace, retail, and other external sources.
• Build acquisition systems that remain reliable as external websites, applications, APIs, and data contracts evolve.
• Handle real-world source complexity such as sessions, tokens, pagination, dynamic content, rate limits, retries, concurrency, and partial failures.
• Build resilient and maintainable acquisition systems with testing, idempotency, deduplication, retries, safe reruns, data-quality validation, monitoring, and alerting.
• Operate acquisition workloads using workflow orchestration, compute, data storage/warehousing, and cloud infrastructure.
• Continuously improve reliability, scalability, maintainability, and total cost of ownership; evaluate build-vs-buy for external data.
• Explore new technologies and AI-assisted development to improve data pipelines.
• Collaborate with Pricing, Data Warehouse Engineering, Data Analysts, and other stakeholders to turn external-data needs into platform capabilities.

Skills

Python

Web scraping

HTTP APIs

Browser debugging

Requests/HTTPX

Selenium

Playwright

Scrapy

SQL & Data warehousing

Cloud infrastructure

Tools

Selenium

Playwright

Scrapy

Requests/HTTPX

Job description

About this Position

As a Data Platform Engineer — External Data Acquisition, you will build and operate ASTRO's platform for acquiring data from external sources, including websites, web/mobile applications, APIs, public datasets, and third-party data providers.

A significant part of this role focuses on production-grade web and application data acquisition for pricing and market intelligence use cases. You will own the acquisition layer—from understanding external systems and extracting data to delivering reliable landing data for downstream processing.

Focus

External Data Acquisition

• Web & App Scraping
• Python
• HTTP/API
• Data Pipelines
• Reliability

As our Astronaut, your missions are:

• Build and maintain reliable web/app crawlers, scrapers, and external API integrations across e-commerce, marketplace, retail, and other external sources.
• Build acquisition systems that remain reliable as external websites, applications, APIs, and data contracts evolve.
• Handle real-world source complexity such as sessions, tokens, pagination, dynamic content, rate limits, retries, concurrency, and partial failures.
• Build resilient and maintainable acquisition systems with appropriate testing, idempotency, deduplication, retries, safe reruns, data-quality validation, monitoring, and alerting.
• Operate acquisition workloads using appropriate workflow orchestration, compute, data storage/warehousing, and cloud infrastructure.
• Continuously improve reliability, scalability, maintainability, and total cost of ownership, including evaluating build-vs-buy approaches for external data.
• Explore new technologies and AI-assisted development or automation to improve how external-data pipelines are built, operated, and maintained.
• Collaborate with Pricing, Data Warehouse Engineering, Data Analysts, and other stakeholders to turn external-data needs into sustainable platform capabilities.

Minimum Qualifications

In order to launch successfully, you need to have:

• Strong Python/software engineering fundamentals and experience building maintainable production systems.
• Hands-on experience building or operating web scraping, crawling, external API, or similar data acquisition systems.
• Strong understanding of HTTP, APIs, JSON, headers, cookies, sessions, authentication, pagination, and request/response behavior.
• Hands-on experience with browser/network debugging and the ability to investigate how websites or applications communicate with their backend services.
• Experience with both HTTP-based extraction and browser automation, using tools such as Requests/HTTPX, Selenium, Playwright, Scrapy, or equivalent.
• Understanding of production reliability patterns such as retry, timeout, rate limiting, concurrency, idempotency, and failure recovery.
• Solid understanding of SQL, data storage/warehousing, schema evolution, workflow orchestration, containerized workloads, and cloud infrastructure fundamentals.
• Strong troubleshooting skills, especially when working with frequently changing external systems outside your direct control.

Good to Have

• Experience acquiring data from mobile applications, marketplaces, e-commerce, grocery, food-delivery, or other large consumer platforms.
• Experience with asynchronous or distributed acquisition systems and high-volume crawling.
• Familiarity with proxy infrastructure, data observability, CI/CD, and infrastructure-as-code.
• Experience using AI-assisted development or automation to improve data acquisition workflows.
• Experience designing reusable scraping frameworks or shared acquisition platforms.
• Experience with geospatial or other non-traditional external datasets.