The core mission of Amazon Web Services (AWS) Field Marketing is to educate customers about cloud computing and our services. Millions of customers engage with us every day across multiple channels. Imagine building a platform that enables AWS to speak to engineers, CTOs, CIOs, and CEOs, educate them about AWS services, and empower them on their journey to the cloud. Our services act as the foundation for announcing new AWS products and are uniquely positioned to redefine how our cloud community consumes information and engages with AWS.
Would you like to support increasing customer base and the revenue for AWS, a market-leading cloud offering? Would you like to be part of a team focused on increasing awareness and adoption of the AWS platform by analyzing customer’s behavior on and outside AWS websites? Do you want to empower our AWS Field Marketing team make data-driven decisions that further establish AWS as leader in the cloud computing world?
As a Data Engineer at AWS, you will be working in a large, extremely complex and dynamic data warehousing environment. We are looking for someone with the uncanny ability to integrate multiple heterogeneous data sources with AWS Field Marketing Data Warehouse and build efficient, flexible, and scalable data warehouse and reporting solutions. You should be enthusiastic about learning new technologies and be able to implement solutions using these technologies to enable upgrades of the existing platform. You should have excellent business and communication skills and be able to work with business owners to develop and define key business questions, then build the data sets that answer those questions. You should be expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing reporting applications. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive growth.
At AWS, you have control over every layer you build. Instead of owning a small slice of an existing service, you will own a core segment of a growing marketing platform serving 1000s of internal customers and millions of external customers. You will build on multiple AWS services and have opportunities to engage directly with those teams to improve our core offerings. At AWS, we work with our customers on a daily basis to prove out our ideas, gather feedback, and improve the platform.
Location: Position may be located in Seattle (preferred), or near any Amazon/AWS U.S. Corp office only. Relocation offered from within the US only to these locations.
· Design, implement, and support a platform providing ad-hoc access to large datasets
· Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
· Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
· Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
· Interface with business customers, gathering requirements and delivering complete reporting solutions
· Build and deliver high quality datasets to support business analyst and customer reporting needs
· Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
· 3+ years of work experience with ETL, Data Modeling, and Data Architecture
· 3+ years of work experience in writing and optimizing SQL
· 2+ years of work experience with reporting tools such as QuickSight/Tableau/PowerBI/etc
· 2+ years of experience in Python or any general purpose scripting language
· Knowledge of distributed systems as it pertains to data storage and computing
· Masters or Bachelor degree in Computer Science or related technical field.
· Industry 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.
· Experience in ETL optimization, designing, coding, and tuning data processes.
· Exceptional troubleshooting and problem-solving abilities.
· Experience with building data pipelines and applications to stream and process datasets at low latencies.
· Experience handling data – tracking data lineage, ensuring data quality, and improving discoverability of data.
· Experience with Amazon Redshift or other distributed computing technology.
· Experience with native AWS technologies for data and analytics such as Redshift Spectrum, Athena, S3, Glue, etc is a bonus.
· Hands-on experience with cloud computing and UNIX/Linux based systems.
· Demonstrated ability to work effectively across various internal organizations.
· Excellent written and verbal communications skills.
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