Sr Data Engineer, Aws Data Platform

5 days ago


Dublin, Dublin City, Ireland Amazon Full time

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry.
As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

Each day, thousands of developers make trillions of transactions worldwide on our cloud.
Almost all of them are harnessing the power of Amazon Web Services (AWS) to enable innovative applications, websites, and businesses.
We store all these transactions for analysis and reporting.

Amazon Web Services is seeking an outstanding Data Engineer to join the AWS Data Lake team.
has a culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable.

The AWS Data Platform team's mission is to help customers to see and understand their use of the AWS Cloud.
We collect and process billions of usage transactions every day into actionable information in the Data Lake and make it available to our internal service owners to analyze their business and service our external customers.

We are truly leading the way to disrupt the data warehouse industry.
We are accomplishing this vision by leveraging relational database technologies like Redshift along with emerging Big Data technologies like Elastic Map Reduce (EMR) to build a data platform capable of scaling with the ever-increasing volume of data produced by AWS services.
The successful candidate will shape and build AWS' data lake and supporting systems for years to come.

You should have deep expertise in the design, creation, management, and business use of large datasets, across a variety of data platforms.
You should have excellent business and communication skills to work with business owners to understand data requirements, and to build ETL to ingest the data into the data lake.
You should be an expert at designing, implementing, and operating stable, scalable, low-cost solutions to flow data from production systems into the data lake.
Above all, be passionate about working with vast data sets and someone who loves to bring datasets together to answer business questions and drive growth.

Key job responsibilitiesDesign, 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.Drive programs and mentor resources to build scalable solutions aligning to team's long term strategy. BASIC QUALIFICATIONS- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
PREFERRED QUALIFICATIONS- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses

Posted: January 28, 2025 (Updated about 1 hour ago)
Amazon is committed to a diverse and inclusive workplace.
Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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