Sr. Data Engineer, AWS WWFE - Analytics, Reporting, Operations and Governance

Amazon Web Services (AWS) is obsessed with ensuring the success of our customers. To this end, AWS is building the industry's best-trained sales force. As the number of AWS sellers and cloud services continues to expand rapidly, AWS is re-inventing how to train and enable its sellers. AWS's Worldwide Field Enablement (WWFE) organization is driving this transition by pioneering highly innovative, multi-modal enablement that is able to support our field's diverse learning styles.

WWFE is looking for a results-oriented Sr. Data Engineer to help AWS build our next generation enablement data management solution.

Key job responsibilities

The Senior Data Engineer will:

Collaborate with WWFE's business leaders and economists to identify data engineering requirements

Lead the technical design of WWFE's reporting, analysis and data management solutions

Collaborate with AWS's Business Technology & Solutions team to leverage best practices and partner on solution designs

Lead and coach junior data engineers on the best practices

Build robust and scalable data integration (ETL) pipelines using SQL/EMR/Python

Work with other AWS Region Services Business Intelligence Teams to integrate into existing data warehouses and plan for scaling into data lake solutions

Design, develop and maintain scaled, automated, user-friendly systems that supports Business Intelligence Engineers to build reports and dashboards

Improve overall data architecture using innovative approaches and new processes from AWS stack or open source

Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation

A day in the life

As a WWFE Sr. Data Engineer, you will be empowered to innovate on a daily-basis with access to any tools you believe will do the job at hand best. You will be supported by a diverse team of fellow DEs, BIs, SDEs, and PMs. Your work will directly enable the data solutions for all of WWFE and will include, though not limited to, setting up and managing data infrastructure (Redshift, Aurora, Airflow, S3 etc.), enabling data self-serve for tech stakeholders and developing the backend logic (typically in Python) for our in-house tools supporting the WWFE business. You will also coach, mentor and learn.

About the team

At AWS, 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.

We are dedicated to supporting our new team members. Our team has a broad mix of experience levels and Amazon tenures, and we're building an environment that celebrates knowledge sharing and mentorship.

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.

BASIC QUALIFICATIONS

- 7+ years of data engineering, database engineering, business intelligence or business analytics experience

- Experience with data modeling, warehousing and building ETL pipelines

- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS

- Experience mentoring team members on best practices

- Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

- Experience with SQL

PREFERRED QUALIFICATIONS

- Experience operating large data warehouses

- Experience with MPP databases such as Amazon Redshift

- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence

- Expertise with cloud infrastructure services (e.g., AWS, Azure, GCP)

- Expertise with NoSQL, OODB, Document, Vector and Relational Databases

- Deep experience leading and influencing the data strategy of your team or organization

- Meets/exceeds Amazon's leadership principles requirements for this role

- Meets/exceeds Amazon's functional/technical depth and complexity for this role

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 $139,100/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.

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