Job
Description
- 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - 4+ years of SQL experience - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc. • Extract huge volumes of structured and unstructured data from various sources (Relational /Non-relational/No-SQL database) and message streams and construct complex analyses. • Develop and manage ETLs to source data from various systems and create unified data model for analytics and reporting • Perform detailed source-system analysis, source-to-target data analysis, and transformation analysis • Participate in the full development cycle for ETL: design, implementation, validation, documentation, and maintenance. 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) Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets 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.
