myGwork | Sr Data Engineer, AWS Data Platform
17 hours ago
DESCRIPTION:
AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.
Each day, thousands of developers make trillions of transactions worldwide on our cloud. Almost all of them are harnessing the power of Amazon Web Services (AWS) to enable innovative applications, websites, and businesses. We store all these transactions for analysis and reporting.
Amazon Web Services is seeking an outstanding Data Engineer to join the AWS Data Lake team. Amazon.com has a culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable.
The AWS Data Platform team's mission is to help customers to see and understand their use of the AWS Cloud. We collect and process billions of usage transactions every 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 leveraging relational database technologies like Redshift along with emerging Big Data technologies like Elastic Map Reduce (EMR) to build a data platform capable of scaling with the ever-increasing volume of data produced by AWS services. The successful candidate will can shape and build AWS' data lake 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 communication skills 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 expert at designing, implementing, and operating stable, scalable, low-cost solutions to flow data from production systems into the data lake. Above all, be passionate about working with vast data sets and someone who loves to bring datasets together to answer business questions and drive growth.
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. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.
Key job responsibilities
• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
• Extract huge volumes of structured and unstructured data from various sources (Relational /Non-relational/No-SQL database) and message streams and construct complex analyses.
• Develop and manage ETLs to source data from various systems and create unified data model for analytics and reporting
• Perform detailed source-system analysis, source-to-target data analysis, and transformation analysis
• Participate in the full development cycle for ETL: design, implementation, validation, documentation, and maintenance.
• Drive programs and mentor resources to build scalable solutions aligning to team's long term strategy
About the team
About AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
BASIC QUALIFICATIONS:
- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience mentoring team members on best practices
PREFERRED QUALIFICATIONS:
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
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