The job in two lines
This role involves building and optimizing data pipelines and processing solutions for Amazon's transportation business, focusing on large-scale data analytics and big data technologies.
Summary by Rezifi's AI, from Amazon’s posting. Years and pay appear only when the posting states them.
What you'd do
- Build end-to-end data pipelines
- Utilize data from disparate data sources
- Evaluate and implement big-data technologies
- Write high performing and optimized SQL queries
- Design and implement automated data processing solutions
Skills it is built around
- data-modeling
- data extraction, transformation and loading tools
- SQL
- bigdata
Required
- cloud/big-data technologies
- Amazon Data Pipeline
- Apache Hadoop
- Apache Hive
- Apache Spark
- EHR/EMR systems
- NoSQL
- data stores
- Object Storage
- document
- key-value
Nice to have
- Amazon Web Services
- Amazon Redshift
- Amazon S3
- aws-glue
- Amazon Kinesis
- FireHose
- AWS Lambda
The facts
- Experience
- 3+ years
- From the posting: “3+ years of data engineering experience”
- Pay
- Not stated
- The posting states no pay.
- Level
- Mid level
- Field
- Data engineering
The full posting
From Amazon’s careers site
As Amazon posted it. See the original
The Amazon ShipTech Analytics organization is looking for a smart and ambitious individual to support the development of analytical tools and data processing solutions for the Amazon transportation business. This role will work within a multi-functional BI and data engineering team with a focus on AMXL (Amazon Extra Large) and other rapidly growing delivery programs where Amazon is innovating to find new ways to deliver to our customers.
The ideal candidate thrives working with large volumes of data, enjoys the challenge of highly complex technical contexts, and is passionate about data and analytics. The candidate is an expert within data modeling, ETL design and cloud/big-data technologies and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates large-scale business impact. The candidate should be a self-starter; comfortable with ambiguity, able to think big, and enjoy working in a fast-paced and global team. It’s a big ask, and we’re excited to talk to those up to the challenge!
Key job responsibilities
· Build end-to-end data pipelines to ingest and transform data from different types of data sources and systems; from traditional ETL pipelines to event data streams
· Utilize data from disparate data sources to build meaningful datasets for analytics, reporting and ML use cases
· Evaluate and implement various big-data technologies and solutions (e.g. Redshift, Hive/EMR, Spark, SNS, SQS, Kinesis) to optimize processing of extremely large datasets
· Understand and analyze business processes, logical data models and relational database implementations
· Write high performing and optimized SQL queries
· Execute research projects, and generate practical results and recommendations
· Design and implement automated data processing solutions and data quality controls
- 3+ years of data engineering experience
- 3+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- 5+ years of data engineering experience
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
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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The ideal candidate thrives working with large volumes of data, enjoys the challenge of highly complex technical contexts, and is passionate about data and analytics. The candidate is an expert within data modeling, ETL design and cloud/big-data technologies and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates large-scale business impact. The candidate should be a self-starter; comfortable with ambiguity, able to think big, and enjoy working in a fast-paced and global team. It’s a big ask, and we’re excited to talk to those up to the challenge!
Key job responsibilities
· Build end-to-end data pipelines to ingest and transform data from different types of data sources and systems; from traditional ETL pipelines to event data streams
· Utilize data from disparate data sources to build meaningful datasets for analytics, reporting and ML use cases
· Evaluate and implement various big-data technologies and solutions (e.g. Redshift, Hive/EMR, Spark, SNS, SQS, Kinesis) to optimize processing of extremely large datasets
· Understand and analyze business processes, logical data models and relational database implementations
· Write high performing and optimized SQL queries
· Execute research projects, and generate practical results and recommendations
· Design and implement automated data processing solutions and data quality controls
Basic qualifications
- Bachelor's degree- 3+ years of data engineering experience
- 3+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Preferred qualifications
- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent- 5+ years of data engineering experience
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
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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