Data Engineer I

Amazon’s interview process for Data Engineer I typically involves three rounds: a technical coding round focusing on SQL and Python, a system design round that tests your ability to architect scalable data pipelines, and an HR round to assess cultural fit. Candidates often face questions on data modeling, ETL best practices, and AWS services. Preparation with real interview questions and mock coding sessions can significantly improve success rates.

Round 1: Technical (Coding + System Design) → Round 2: Technical (Advanced) → Round 3: HR

Amazon fosters a culture of ownership, customer obsession, and continuous learning. Engineers are encouraged to experiment, take calculated risks, and collaborate across teams. While the work pace is fast, Amazon also offers mentorship, internal mobility, and a range of employee resource groups to support work‑life balance.

Bachelor’s degree (B.E/B.Tech/B.Sc) in Computer Science, Information Technology, or related field. Minimum 60% in final year or equivalent. 1+ years of data engineering experience. No backlogs in the final year. Strong academic record and relevant project experience are preferred.

Amazon is one of the world’s leading e‑commerce and cloud computing giants, known for its relentless focus on customer obsession, innovation, and operational excellence. With a presence in over 200 countries, Amazon’s Indian operations have grown rapidly, creating millions of jobs across technology, logistics, and services. The International Seller Services (ISS) Central Analytics team in Bengaluru is a key pillar that empowers sellers worldwide by providing data‑driven insights and tools to scale their businesses. As a Data Engineer I, you will join this high‑impact team and help shape the data infrastructure that fuels Amazon’s global marketplace. Role Summary The Data Engineer I role is designed for early‑career professionals who are passionate about building scalable data pipelines and working with large volumes of data. You will collaborate with data scientists, applied scientists, and economists to deliver reliable, high‑performance data solutions that support machine learning and AI initiatives. Your work will directly influence product decisions that affect millions of sellers and customers. Key Responsibilities 1. Design, develop, and maintain end‑to‑end ETL/ELT pipelines using AWS services. 2. Build and optimize data models for analytics and machine learning workloads. 3. Implement data ingestion routines from diverse sources (APIs, logs, third‑party feeds) into data lakes and warehouses. 4. Ensure data quality, integrity, and security across all stages of the pipeline. 5. Collaborate with cross‑functional teams to translate business requirements into technical specifications. 6. Monitor and troubleshoot production data pipelines for performance and reliability. 7. Automate data workflows using orchestration tools such as AWS Glue, Airflow, or Step Functions. 8. Stay current with emerging big‑data technologies and propose improvements. 9. Document data architecture, pipeline logic, and best practices. 10. Mentor junior engineers and share knowledge within the team. Tech Stack - AWS: S3, Glue, EMR, Redshift, Athena, Lambda, Step Functions - Big Data: Spark, Hive, Hadoop - Databases: Redshift, PostgreSQL, MySQL - Programming: Python, SQL, Bash/KornShell - Tools: Airflow, Git, Docker, CI/CD pipelines Growth Path Starting as a Data Engineer I, you can progress to Data Engineer II, Senior Data Engineer, or lead roles such as Data Engineering Manager or Principal Engineer. Amazon’s culture of continuous learning and internal mobility allows engineers to explore different domains, from cloud infrastructure to AI research. Why Join Amazon? Amazon offers competitive compensation, comprehensive benefits, and a culture that rewards innovation and ownership. Working at Amazon means being part of a global team that tackles complex problems, receives mentorship from industry leaders, and has access to cutting‑edge technologies. The opportunity to impact millions of users and sellers worldwide makes this role uniquely rewarding.