Are you interested in building scalable data structures? Designing and building a DW to scale the main app that impacts the lives of millions of people? Would you like to build solutions to scale the use of data analytics, machine learning to directly improve our users experience?

The A to Z mobile application directly impacts the lives of associates by helping them identify the best shifts for their schedule, opportunities to pick up additional work, and choose when they get paid. We are committed to helping associates achieve the work life harmony that is best for them. We are also committed to helping Amazon acquire, train, and retain associates to fulfill Amazon’s mission to be the world’s most customer centric company.

As a Sr. Data Engineer on the A to Z team you will lead the initiative of structuring, designing, and building the platform’s data warehouse, and spinning up data marts that will help drive different features.

The ideal candidate will have excellent analytical skills and the ability to synthesize data into data stores and data pipelines for use by data scientists, business intelligence engineers, business leaders, and SDEs.

To be successful in this role, you should have broad skills in database design, be comfortable dealing with complex, medium to large data sets, and understand how self-service dashboards are built and used with your data sets.

The successful candidate will have a passion for data and analytics, be a self-starter comfortable with ambiguity, strong attention to detail, an ability to work in a fast-paced and entrepreneurial environment, and driven by a desire to innovate.


· 5+ years of experience as a Data Engineer or in a similar role.
· Experience with Big Data platforms and architecture, relational and no SQL database concepts with advanced knowledge of SQL and its variants
· Experience with data modelling, Data Warehouse/ Datamart design and architectural concepts, ETL/ ELT and reporting/analytic tools and environments, data structures.
· Experience with data modeling, data warehousing, and building ETL pipelines
· Experience in SQL, and query optimization methods.
· Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, Finance or related field.
· Hands on experience with Python/Scala, writing complex data transformations in spark and automating pipelines.
· Comfortable using AWS services such as EMR(Hive/Spark), Redshift, S3, Glue, Cloudformation.
· Experience with data storage/compression on Hadoop file systems S3 (EMRFS)/HDFS



· Master’s degree in related field (Mathematics, Statistics, Computer Science, Finance, Economics or similar quantitative field)
· Industry experience as a Data Engineer, Business Intelligence Engineer, Data Scientist, or related field with a track record of manipulating, processing, and extracting value from large datasets.
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Hands on experience with implementing scalable Data Lakes with real-time, near real-time, and batch processing use cases.
· Excellent knowledge of Advanced SQL working with large data sets.
· Experience building data products incrementally and integrating and managing datasets from multiple sources.
· Experience with AWS Technologies including (S3, Redshift, Tableau Server Deployment & Maintenance , Quicksight, etc.).
· Familiarity with AWS Data Pipelines/Lambda/DynamoDB/Airflow
· Comfortable with Linux environments.