Data Engineer II, International Seller Growth
Amazon Hyderabad, Telangana, India
Software Development · 10,001+ employees
About the role
The role involves constructing and maintaining complex ETL pipelines and data models to support international seller growth. You will also be responsible for enforcing data quality standards and collaborating with analysts to facilitate data-driven decision-making.
What they look for
Requirements
Candidates must have at least 3 years of data engineering experience and 4 years of SQL experience. A bachelor's degree is required, along with proficiency in AWS data services and scripting languages like Python or Scala.
Full description
Join Us in the International Seller Services Central Analytics Team !!
We are a dedicated group of Engineers within the Seller Services organization at Amazon. Our mission is to deliver data-driven analytical solutions that empower sellers to thrive on Amazon's global platform. We specialize in constructing and maintaining intricate data pipelines that facilitate the seamless integration of data into Amazon's internal tools and teams.
We are currently in search of a brilliant, self-driven, and seasoned Data Engineer/Developer to join our team. In this role, you will have the opportunity to work on building scalable solutions, including extensive data models and complex ETL pipelines that serve our GenAI ready data layer.
You will be immersed in a substantial business challenge, tasked with creating architecture, designing documents, constructing logical and physical data models, and building intricate ETL pipelines. All of this will be accomplished using a suite of AWS tools such as Lambda, Redshift, S3, DynamoDB, Glue, and Hive. Additionally, you will be an integral part of a team dedicated to supporting the ISS organization in maintaining and facilitating easy access to our definitive source of metric data.
Key job responsibilities
- Construct intricate ETL pipelines utilizing Datanet (Redshift) and Craddle (Spark Sql ).
- Create and manage datasets within AWS Dynamo DB, AWS S3, and Amazon Redshift.
- Develop complex ETL workflows employing AWS Glue.
- Orchestrate step functions through Python / Scala.
- Implement and enforce rigorous data quality standards and data governance policies, ensuring data accuracy, consistency, and security. Establish procedures for data validation, cleansing, and lineage tracking.
- Continuously monitor and optimize data pipelines and processes to enhance performance and efficiency. Identify bottlenecks and implement enhancements to expedite data processing and minimize latency.
- Collaborate closely with data analysts and visualization experts to facilitate data-driven decision-making. This includes designing and maintaining data reporting and visualization solutions.
- Demonstrate profound expertise in AWS data services, including Amazon S3, Glue, EMR, Redshift, Athena, and more. Select the most appropriate services for specific data engineering tasks and leverage their capabilities effectively.
- Develop and maintain mission-critical applications extensively used by sellers worldwide.
- Have good knowledge on scripting using either Python or Scala
Basic Qualifications: - 3+ years of data engineering experience - 4+ years of SQL experience - Experience with data modeling, warehousing and building ETL pipelines - Bachelor's degree
Preferred Qualifications: - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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