Job Information
Amazon Sr. Data Engineer, Sales Insights and Data Science in Seattle, Washington
Description
Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (“cloud computing”). With AWS, you can procure compute power, storage, and many other services – gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform.
As a Sr. Data Engineer within SMGS Ops, you will be working in a large, complex, and dynamic data environment. We are looking for an experienced Data Engineer with an uncanny ability to integrate multiple heterogeneous data sources to build efficient, flexible, and scalable data warehouse and reporting solutions. The ideal candidate has deployed analytics platforms to 5000+ users, optimizing the architecture for performance and positive end-user experience. You are enthusiastic about learning new technologies and implementing solutions using these technologies to empower internal customers and scale the platform. You demonstrate solid communication skills and the ability to partner with Research Scientists and business owners across technical and non-technical teams to develop and define key business questions, then build the solutions that answer those questions.
In this role, you will serve as the expert in designing, implementing, and operating a stable, scalable, low cost environment to flow information from the data warehouse into end-user facing reporting applications such as Tableau or AWS QuickSight. Above all, you will bring large datasets together to answer business questions and drive data-driven decision making. This role will build the engineering infra & data products for Startup (SUP) business teams, work with 3p data acquisition and SUP business development (BD) teams
Key job responsibilities
Plan, design, implement, and manage a deployment of self-service data visualization platform (with front end as Tableau, QuickSight, and/or Apache Superset)
Design, build, and maintain data pipelines using modern Big Data technologies such as AWS Redshift, S3, Glue, Athena, EMR, Spark, Hive, etc.
Utilize modern cloud database and storage concepts to for data storage and versioning (Data Lakes with AWS S3)
Establish scalable, efficient, automated processes for large scale data analysis
Build data pipelines to feed machine learning models for real-time and large-scale offline use cases.
Support the development of performance dashboards that encompass key metrics to be reviewed with senior leadership and sales management
Work with business owners and partners to build data sets that answer their specific business questions
Support Sales Operations Leads, Analysts and beyond in analyzing usage data to derive new insights and fuel customer success
About the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.
Why 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.
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.
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.
About Sales, Marketing and Global Services (SMGS)
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
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
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $123,700/year in our lowest geographic market up to $240,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.