Sr. Data Engineer, AWS Enterprise Support Strategy and Planning

Job summary
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 with AWS Enterprise Support, 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 Data 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.



About Us

Inclusive Team Culture
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 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. Our senior 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.


Key job responsibilities
Key responsibilities include:

• 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, Hammerstone, 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 Business Operations Leads, Analysts and beyond in analyzing usage data to derive new insights and fuel customer success.
• 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.

A day in the life
In this role, you will serve as the expert in designing, implementing, and operating a stable, scalable, single source of truth 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.

Basic Qualifications

Basic Qualifications

• Bachelor degree in Computer Science or related technical field.
• 5+ years of experience as a Data Engineer or in a similar role.
• Strong SQL skills to query relevant datasets.
• Experience with one of the functional scripting languages (Python, Scala etc.) to process semi-structured or unstructured data inputs.
• Experience with data modeling, data warehousing, and building ETL pipelines.
• Knowledge of data management fundamentals and data storage principles.
• Knowledge of distributed systems as it pertains to data storage and computing.
• Ability to complete projects timely, accurately and with strong attention to detail, with continuous communication of progress updates to stakeholders.

Preferred Qualifications

Preferred Qualifications

• 7+ years of experience as a Data Engineer, BI Engineer, Business/Financial Analyst or Systems Analyst in a company with large, complex data sources.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets.
• Demonstrated strength in data modeling, ETL development, and data warehousing.
• Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
• Experience providing technical leadership and mentoring other engineers for 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.
• Demonstrated ability to work effectively across various internal organizations

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $154,545/year in our lowest geographical market, up to $229,998/year in our highest geographical market. Pay is based on market location and may vary depending on job-related knowledge, skills, and experience. A sign-on payment and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via our internal or external careers site.


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.