Description Amazon Web Services is seeking an extraordinary Data Engineer to join the AWS Data Platform team. Our teams take on some of the hardest scalability, performance, and distributed computing challenges the world. We process trillions of events per month using stream processing techniques (Kinesis), process billions of line items via map reduce (EMR) and handle artifacts through the latest in database technologies (DynamoDB and Aurora). We process big data and provide tools for customers to interactively understand their bills. We also provide the analytics that let customers handle billions of dollars of IT usage and spending. Because we sit at the nexus of all AWS services and interact directly with end-customers, we also work closely across all AWS teams to ensure that we offer a great customer experience. The AWS Data Platform team's vision is to help customers handle the full life cycle of data at all levels of granularity, simplify data collection, integration, and aggregation of AWS data assets, and provide services (compute, storage, security) to access datasets at scale. We collect and process billions of usage and billing transactions every single day into actionable information in the Data Lake and make it available to our internal service owners to analyze their business and service our external customers. We are truly leading the way to disrupt the data warehouse industry. We are accomplishing this vision by bringing to bear Big Data technologies like Elastic Map Reduce (EMR) and Spark in addition to data warehouse technologies like Redshift to build a data platform capable of scaling with the ever-increasing volume of data produced by AWS services. You will have the ability to craft and build AWS' data lake platform and supporting systems for years to come. You should have deep expertise in the design, creation, management, and business use of large datasets, across a variety of data platforms. You should have excellent business and interpersonal skills to be able to work with business owners to understand data requirements, and to build ETL to ingest the data into the data lake. You should be an authority at crafting, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data lake. 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. Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. We offer flexibility in working hours and encourage you to find your own balance between your work and personal life. Basic Qualifications - 5+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Experience with Apache Spark / Elastic Map Reduce Preferred Qualifications - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) 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 https://www.amazon.jobs/en/disability/us.