**Experienced Full Stack Data Engineer – Web & Cloud Application Development for Amazon's Accounting BI Group**

**Job Description** **Introduction** At Amazon, we're revolutionizing the way the world shops, communicates, and accesses information. As a leader in the e-commerce industry, we're constantly pushing the boundaries of innovation and technology. Our Accounting BI group is a key player in this journey, helping us automate and improve our accounting processes, develop advanced reporting solutions, and provide timely and accurate financial data to our stakeholders. We're seeking an experienced Full Stack Data Engineer to join our team and contribute to our mission of making Amazon the most customer-centric company in the world. **About the Role** As a Full Stack Data Engineer on our Accounting BI team, you'll play a critical role in designing, building, and implementing data infrastructure, data availability, and access to client insights across the company. You'll work closely with stakeholders and engineering groups to scope and implement the right data structure and generation to facilitate the evaluation of key Amazon customer behavioral questions. Your expertise in data engineering, data modeling, warehousing, and ETL pipelines will help us drive business growth and improve our customers' shopping experience. **Responsibilities** * Collaborate with stakeholders and engineering groups to identify and scope the right data structure and generation for use to facilitate the evaluation of key Amazon customer behavioral questions. * Partner with partner engineering groups to enhance data infrastructure, data availability, and access to client insights made available through BI tools across the company. * Design, build, and implement the right ETL methods using AWS and similar technologies. * Implement anomaly detection structures to proactively address potential data quality issues using industry-preferred frameworks. * Enable big-scale analytics using EMR and other large-data technologies. * Establish and implement data quality practices that should be followed across the company. * Work on proof-of-concepts for the adoption of new technologies and tools. **Key Qualifications** * 3+ years of data engineering experience. * Experience with data modeling, warehousing, and building ETL pipelines. * Experience with SQL. * Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala). * Experience with one or more scripting languages (e.g., Python, KornShell). * Experience with large data technologies such as Hadoop, Hive, Spark, EMR. * Experience with large data processing technologies (e.g., Hadoop or Apache Spark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments. **Preferred Qualifications** * Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud). * Experience with big data processing frameworks (e.g., Apache Spark, Hadoop). * Experience with data visualization tools (e.g., Tableau, Power BI). * Experience with agile development methodologies (e.g., Scrum, Kanban). **Benefits** * Medical, dental, and vision coverage. * Maternity and parental leave options. * Paid time off (PTO). * 401(k) plan. * Opportunities for professional development and growth. * Collaborative and inclusive work environment. * Flexible work arrangements (remote work options). * Access to cutting-edge technologies and tools. * Opportunities to work on high-impact projects and contribute to Amazon's mission. **Why Join Amazon as a Remote Worker?** Joining Amazon as a remote employee offers numerous key advantages, reflecting our commitment to fostering a dynamic and inclusive work environment. Some of the exceptional benefits of joining Amazon as a remote employee include: * Flexibility: Remote work gives you the power to manage your work schedule and location, allowing for better work-life stability and the ability to work from any location with a strong internet connection. * Global opportunities: Amazon's remote work options can open up opportunities to collaborate with various teams and experts from diverse locations worldwide, allowing you to interact with an international team of workers and expand your professional network. * Reduced commute: Eliminating the need for daily commutes saves time and reduces the stress related to traveling to and from the office, contributing to improved productivity and overall well-being. * Autonomy and independence: Remote work often promotes a sense of autonomy, allowing employees to take ownership of their tasks and manage their work independently while aligning with Amazon's organizational goals and values. * Technology integration: Amazon provides remote employees with access to modern technology and communication tools, facilitating seamless collaboration and ensuring that remote employees have the necessary resources to excel in their roles. * Professional development: Despite working remotely, Amazon emphasizes professional development and growth, offering opportunities for skill-building, education programs, and professional development projects for its remote team members. * Workplace wellness: Amazon places significance on employee well-being, offering resources and support for remote employees to maintain a healthy work-life balance and access wellness programs that promote physical and mental well-being. * Collaboration tools: The company provides access to collaborative structures and tools that enable effective communication, task management, and teamwork, fostering a cohesive remote working environment. * Inclusive work culture: Amazon fosters an inclusive work culture that values diversity, equality, and inclusion, ensuring that remote employees have the same opportunities to contribute to the company's mission and success from any location. **How to Apply** If you're a motivated and experienced data engineer looking to join a dynamic team and contribute to Amazon's mission, we encourage you to apply for this exciting opportunity. Please submit your resume and a cover letter outlining your qualifications and experience. We look forward to hearing from you! Apply for this job