Address
Form of work
Salary- 1+ years of Data Engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
Do you have deep expertise in the end to end development of large datasets across a variety of platforms? Are you great at designing data systems and redefining best practices with a cloud-based approach to scalability and automation? In this role, you will be responsible for scaling our existing infrastructure, incorporating new data sources, and building robust data pipelines for production level systems. In partnership with product and business teams, you will work backwards from our business questions to drive scalable solutions. You will be a technical leader owning the architecture of our data platform and influence best practices across multiple teams. Above all, you should be passionate about working with data to answer business questions and drive growth.
Key Responsibilities Include:
- Design, implement, and maintain a cutting-edge cloud-based data-infrastructure for large data-sets.
- Develop and optimize data tables using best practices for partitioning, compression, compaction, etc.
- Develop and support ETL pipelines with robust monitoring and alarming
- Maintain data integrity, availability, and auditability. Manage AWS resources. Drive the adoption of new technologies and new best practices
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our organizations members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Work life balance
Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.
Inclusion
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.
Key job responsibilities
As a Data Engineer you will be working in one of the world's largest and most complex data warehouse environments. You should be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets. You will build data analytical solutions that will address increasingly complex business questions
You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion.
You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training.
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with database, data warehouse or data lake solutions
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $81,000/year in our lowest geographic market up to $185,000/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.
