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Amazon Web Services BI Data Engineer in Seattle, Washington

Description

The AWS Developer Relations Team is looking for an experienced Data Engineer. As a Data Engineer, you will need to review technical design, develop and enhance data systems and pipelines supporting process, as well as integrate in-house data infrastructure with partner systems. You should be an expert in the architecture of data warehousing solutions, using multiple platforms and tools. In addition, you should have strong analytical skills and excel in the design, creation, management, and business use of large data sets, combining raw information from different sources. Similarly, you will be responsible for designing and implementing scalable extract, transform, and load (ETL) processes to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as a service, which will have an immediate influence on day-to-day business decision making. Moreover, you will create automated alarming and dashboards to monitor data integrity. Finally, yet importantly, you should have very good communication skills and ability to adjust communication to different groups of stakeholders, collaborating with architects, BI engineers, data scientists, business analysts/managers, to evaluate business needs and objectives in order to set up the best data management environment. Overall, you will be the subject matter expert for the data structures and usage, while striving for efficiency by aligning data systems with business goals.

You will develop new data engineering patterns that leverage new cloud architectures, and will extend or migrate existing data pipelines to the architectures as needed. You will be responsible for designing and implementing the complex ETL pipelines in data warehouse platform and other BI solutions to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making at Amazon.com

About Us

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and 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.

Work/Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

Job responsibilities

  • Design, implement and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power

  • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies

  • Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.

  • Enjoy working closely with your peers in a group of very smart and talented engineers.

  • Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

  • Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency

BASIC QUALIFICATIONS

  • Bachelor’s Degree in Computer Science/Engineering, Informatics, Mathematics, or a related technical discipline

  • 5+ years of industry experience in data engineering, data science, business intelligence or related field

  • Knowledge of data management fundamentals and data storage principles

  • Demonstrated strength in data modeling, ETL development, and data warehousing/lakes

  • Database design and administration experience with various RDBMS, such as MS SQL Server, PostgreSQL, MySQL, etc.

  • Experience architecting data solutions with AWS products including Big Data Technologies (Redshift, RDS, S3, Glue, Athena, EMR, Spark, Hive, etc.) and/or Microsoft Database Software Stack (SQL Server/SSIS/SSAS)

  • Experience using business intelligence reporting tools (AWS QuickSight, Power BI, Tableau, etc.)

  • Advanced SQL and query performance tuning skills.

  • Experience building data products incrementally, integrating and managing large data sets from multiple sources

  • 2+ year of coding experience with modern programming or scripting language (Python, Scala, Java, etc.).

PREFERRED QUALIFICATIONS

  • Master’s Degree in Data Engineering, Applied Data Science, Data and Web Science, or related certification

  • Knowledge of systems engineering to optimize integration of data service/software solutions with data infrastructure

  • Proven track record of applying data engineering for enabling business analytics (Engineering, Operations, Finance, etc.)

  • Experience providing technical leadership and mentoring other engineers for the best practices on data engineering

  • Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

  • Experience using AWS Data services such as AWS Glue, Amazon Redshift, AWS Data Pipeline, Amazon QuickSight, etc.

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.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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