Data Engineer I
Amazon
Job Description
- For the Amazon Recruitment 2026 drive, the team is seeking a smart and highly motivated Data Engineer. You will provide technical leadership and build end-to-end analytical solutions that are highly available, scalable, stable, and secure.
- You will work with huge datasets and architect advanced data ecosystems. The role involves implementing data ingestion routines using best practices in data modeling and ETL/ELT processes by leveraging AWS technologies .
Key Responsibilities
- As a Data Engineer I at Amazon, your key responsibilities will include:
- Pipeline Development: Designing, implementing, and operating large-scale, high-volume data structures for analytics and data science.
- Data Ingestion: Implementing data ingestion routines using best practices in ETL/ELT.
- AWS Integration: Integrating data systems with AWS tools to support customer use cases.
- Optimization: identifying opportunities in existing data solutions for improvements and adopting best practices in data integrity.
- Collaboration: Collaborating with engineers to translate business requirements into robust, scalable solutions.
Skills & Eligibility
- To be eligible for Amazon Recruitment 2026, candidates must meet the following criteria:
- Educational Background: B.E / B.Tech / B.Sc in Computer Science or related fields.
- Experience: 1+ years of data engineering experience.
- Mandatory Technical Skills: Experience with Data Modeling, Warehousing , and building ETL pipelines . Proficiency in SQL and query optimization for large-scale datasets. Experience with scripting languages like Python or KornShell .
- Experience with Data Modeling, Warehousing , and building ETL pipelines .
- Proficiency in SQL and query optimization for large-scale datasets.
- Experience with scripting languages like Python or KornShell .
- Preferred Qualifications: Experience with Big Data technologies: Hadoop, Hive, Spark, EMR . Knowledge of ETL tools (Informatica, Glue, etc.). Familiarity with AWS ecosystem.
- Experience with Big Data technologies: Hadoop, Hive, Spark, EMR .
- Knowledge of ETL tools (Informatica, Glue, etc.).
- Familiarity with AWS ecosystem.
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