Data Engineer II, DBS BI

AWS Databases, Analytics and AI/ML Products and Services is one of the largest and fast-growing business unit within AWS. We are working to rebuild and revolutionize data engineering and business intelligence systems within database, analytics and AI/ML organization to support fast growing business needs.

We are looking for experienced, self-driven Data Engineer. In this role, you will be building complex data engineering and business intelligence applications using AWS big data stack. You should have deep expertise and passion in working with large data sets, data visualization, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You should have excellent business acumen and communication skills to be able to work with business owners to develop and define key business questions and requirements. You will provide guidance and support for other engineers with industry best practices and direction. Amazon Web Services (AWS) has culture of data-driven decision-making, and demands timely, accurate, and actionable business insights.

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 their cloud services.

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.
• Develop and manage ETLs to source data from various commercial, sales and operational systems and create unified data model for analytics and reporting.
• Use business intelligence and visualization software (e.g., QuickSight.) to develop dashboards those are used by senior leadership.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Work with Product Managers, Finance, Service Engineering Teams and Sales Teams on day-to-day basis to support their new analytics requirements.
• Manage numerous requests concurrently and strategically, prioritizing when necessary
• Partner/collaborate across teams/roles to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.

About the team
A day in the life
The SageMaker Engines team develops technology for supporting training of Deep Learning models at large scale. This entails implementation of model parallelism and memory saving techniques to allow training of models across accelerators as well as implementation of network communication collectives optimized for the AWS infrastructure.

About the team
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 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.

EEO/Accommodations
AWS is committed to a diverse and inclusive workplace to deliver the best results for our customers. For individuals with disabilities who would like to request an accommodation, please let us know and we will connect you to our accommodation team. You may also reach them directly by visiting https://www.amazon.jobs/en/disability/us.

Basic Qualifications

- Bachelors or Master’s Degree in Computer Science/Engineering, Information Technology with at least 6+ years of experience in Data Engineering Applications with following skills:
- Excellent knowledge and experience of designing and developing data engineering systems from grounds up and maintaining/supporting existing systems.
- Excellent knowledge of ETL tools and various data processing techniques
- Excellent knowledge of data warehousing and big data design and concepts
- Experience in dealing with large and complex data sets and performance tuning
- Experience in designing data models that supports structures and unstructured data
- Experience in gathering requirements and formulating business metrics for reporting
- Strong verbal/written communication & presentation skills, including an ability to effectively communicate with business: technical and technical teams.
- Ability to deal with ambiguities and competing priorities.

Preferred Qualifications

- Prior experience in AWS stack including Glue Crawler, Glue Catalog, Glue Pipelines, Lake Formation, Redshift, QuickSight, EMR/Hive, Spark, Scala,
- Prior experience in programming using Python
- Experience with AWS as cloud
- AWS certification will be plus.
- Any knowledge/skill on Data Science, AI/ML will be plus

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/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.