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Salary
$33k – $64k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 4+ years exp
Overview
Company
Impact
Profile match
Amazon is an American technology and retail conglomerate founded by Jeff Bezos in 1994 as an online bookstore and headquartered in Seattle, Washington. It operates the world's largest online marketplace together with a global logistics network, physical grocery stores and a third-party seller platform that accounts for most units sold. Amazon Web Services, launched in 2006, is the leading public cloud provider and generates the majority of the group's operating profit, while advertising, Prime Video, Alexa devices and Kuiper satellite broadband round out the business.

We are seeking a Senior Data Engineer with 4+ years of experience in building scalable, distributed, and high-performance data systems. In this role, you will architect, develop, and optimise real-time pipelines and analytical systems that enable Amazon teams to extract actionable insights and power intelligent decision-making across the organisation.

Responsibilities:

  • Design, build, and maintain real-time and batch data pipelines for structured and unstructured datasets.
  • Develop scalable data ingestion, transformation, and processing frameworks for high-volume data environments.
  • Collaborate with product, analytics, and infrastructure teams to ensure data reliability, availability, and performance.
  • Build APIs and data models that support large-scale analytics and machine learning applications.
  • Optimise query performance, storage systems, and ETL workflows for massive datasets.
  • Mentor junior engineers, contribute to best practices, and lead design reviews for critical data infrastructure.

Requirements:

  • 4+ years of experience in data engineering, backend development, or large-scale data systems.
  • Strong proficiency in Python; experience with Java or Scala is a plus.
  • Hands-on experience with real-time processing frameworks such as Kafka, Spark Streaming, or Flink.
  • Solid understanding of data modelling, distributed systems, and API integrations.
  • Proficiency with SQL and NoSQL databases and working experience on AWS (S3 EMR, Redshift, Glue, Kinesis).
  • Familiarity with web scraping frameworks (Scrapy, Selenium, Playwright) or similar data acquisition tools.
  • Experience in optimising ETL pipelines and handling large-scale datasets.

Preferred Qualifications:

  • Experience in AI/ML data pipelines or analytical dashboarding.
  • Exposure to workflow orchestration tools (Airflow, Step Functions, or similar).
  • Experience mentoring engineers or leading small technical teams.
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