We’re looking for Data Engineer to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! We own a world-class data lake that is used to drive multi-billion dollar decisions on a regular cadence and we're looking to improve on filling the lake quickly, with as little human intervention needed and democratize the data in the lake.

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Key job responsibilities

• Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS.

• Implement and support reporting and analytics infrastructure for internal business customers.

• Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging.

• Develop data objects for business analytics using data modeling techniques.

• Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.

• Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.

• Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions.

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Basic Qualifications

- 1+ years of data engineering experience
- 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, Computer Engineering, or related fields

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Preferred Qualifications

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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About the company

Amazon

Company overview

Amazon runs a wide set of consumer and enterprise businesses, including online retail, Prime Video and other subscription services, advertising, devices, and Amazon Web Services (AWS). Amazon also builds large-scale software and infrastructure for logistics, payments, and cloud computing, and hires across engineering, product, operations, corporate functions, and frontline roles. Amazon’s early-career hiring spans both office-based teams and operational sites, which means “entry-level” can look very different depending on the org.

Locations and presence

Amazon has major corporate hubs in Seattle and Arlington (HQ2) plus large engineering and operations sites across North America, EMEA, and Asia-Pacific. For many corporate roles, Amazon’s stated expectation has shifted to five days per week in-office for office-based employees (with exceptions depending on role and site).

Palpable Score

76.7

/ 100

Amazon is one of the most accessible early-career employers at scale, with recurring internships and graduate hiring across many disciplines and geographies. Amazon also provides unusually clear public information about interview mechanics and publishes pay ranges on a large share of roles, which supports informed decision-making. The biggest drag on outcomes is the combination of high-performance culture signals and recent corporate job cuts, which adds risk for early-career stability depending on team and org.

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Data Engineer, Data Center Capacity Delivery

Amazon

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Key job responsibilities

Basic Qualifications

Preferred Qualifications

About the company

Amazon

Company overview

Locations and presence

Palpable Score

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