Amazon Off Campus Drive 2023 For Support Engineer/Data Engineer

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Amazon Off Campus Drive 2023 For its Support Engineer/Data Engineer, Amazon Drive is organizing Off Campus Drive for candiates in Any Batch. In odrer to apply, candidates should have degree in Bachelors Degree. If you are interested, Please apply as soon as possible.

Company Name: Amazon

Role: Support Engineer/Data Engineer

Location: Bangalore/Hyderabad

Experience: Freshers

Qualification: Bachelors Degree

Batch: Any Batch

Job Type: Full Time

Salary: Best in Industry

Amazon Off Campus Drive 2023

About Us:

  • Amazon’s India Ad Tech organization is seeking a highly quantitative, enthusiastic Data Engineer to drive the development of Ads analytics and insights.
  • Be a part of an innovative and passionate team, responsible for building a successful, sustainable and strategic international business for Amazon, from the ground up.
  • You will succeed in this role if you are an organized self-starter who can learn new technologies quickly and excel in a fast-paced environment.
  • In this position, you will be a key contributor and partner in developing analytics and insights that global executive management teams and business leaders will use to define Ad strategies and deep dive businesses.
  • You should be highly analytical, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines.
  • You will be comfortable learn new technologies, exploring new areas and diving deep.
  • A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred.
  • You will be working closely with Product managers, program managers, SDEs and UI engineers to build data engineering solution to provide in depth Ad insights, analytics and recommendations and drive India Ad business.


  • 1+ years of data engineering experience
  • Experience with SQL
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
  • Experience with one or more scripting language (e.g., Python, KornShell)
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline. – 1+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets A desire to work in a collaborative, intellectually curious environment. – Effective analytical, troubleshooting, and problem-solving skills


  • – 2+ years of experience as a Data Engineer, BI Engineer or related field in a company with large, complex data sources. – Experience working with AWS big data technologies (Redshift, S3, EMR, Glue) – Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations. – Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space.


  • Design, develop, implement, test, and operate large-scale, high-volume, high-performance data structures for analytics and Reporting.
  • Implement data structures using best practices in data modeling, ETL processes, and SQL, AWS – Redshift, and OLAP technologies, Model data and metadata for ad hoc and pre-built reporting.
  • Work with product tech teams and build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark.
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
  • Interface with business customers, gathering requirements and delivering complete reporting solutions.
  • Collaborate with Analysts, Business Intelligence Engineers, SDEs, and Product Managers to implement algorithms that exploit rich data sets for statistical analysis, and machine learning.
  • Communicate effectively with product/business/tech-teams/other Data teams.

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