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Senior Data Engineer, AWS Infra Automation
Remote in US, TX, Virtual Location - Texas
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Senior Data Engineer, AWS Infra Automation

Job summary
Are you interested in building the next generation Supply Chain Management (SCM) systems that power the AWS cloud? Do you want to revolutionize the way we track the gear that forms the foundation of AWS? Do you want to have direct and immediate impact on millions of customers who use AWS every day?

We’re looking for Data Engineers to help us grow our Data Lake, which is built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more!

Our Data Engineers develops our data models to support our system designs. Our Data Engineers builds analytics solutions for our internal customers to answer questions with data and drive critical improvements for the business. Our Data Engineers use best practices in software engineering, data management, data storage, data compute, and distributed systems. We are passionate about solving business problems with data!

Key job responsibilities
• Develop data models to support system designs.
• 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.
• Develop, test, and deploy code using the SDE Amazon Builder toolset. This includes the code for deploying infrastructure and solutions for secure data storage, ETL pipelines, data catalog, and data query. This is a great way to grow your career here at Amazon.

Basic Qualifications

· Bachelor’s Degree in Computer Science/Engineering, Informatics, Mathematics, or a related technical discipline
· 5+ years of industry experience in data engineering, data science, business intelligence or related field
· Knowledge of data management fundamentals and data storage principles
· Demonstrated strength in data modelling, ETL development, and data warehousing/lakes
· Database design and administration experience with any RDBMS, such as MS SQL Server, PostgreSQL, MySQL, etc.
· Experience architecting data solutions with AWS products including Big Data Technologies (Redshift, RDS, S3, Glue, Athena, EMR, Spark, Hive, etc.) and/or Microsoft Database Software Stack (SQL Server/SSIS/SSAS)
· Advanced SQL and query performance tuning skills.
· Experience building data products incrementally, integrating and managing large data sets from multiple sources
· 3+ year of coding experience with modern programming or scripting language (Python, Scala, Java, etc.).

Preferred Qualifications

· Master's degree in Computer Science / Computer Engineering (or equivalent)
· Strong customer focus, ownership, urgency, and drive
· Success working across organizational boundaries, and bringing together people with diverse perspectives and experience to find solutions
· Experience with data visualization using Tableau, QuickSight, or similar tools
· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
· Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
· Experience providing technical leadership and mentoring other engineers for best practices on data engineering
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

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. For individuals with disabilities who would like to request an accommodation, please visit