Job Description

Job Title Principal Analytics Specialist

Description

Job summary
Do you like to solve complex and large-scale data challenges in the world today? Do you want to have an impact in the development and use of new ways to explore data? Come join us.

Amazon Web Services (AWS) offers a comprehensive set of services to handle every step of the analytics and AI/ML process chain including data warehousing, business intelligence, batch processing, stream processing, log analytics, data workflow orchestration and a comprehensive set of AI/ML services.

We are looking for an Analytics and/or AI/ML Specialized Solutions Architect, who will be the Subject Matter Expert (SME) for helping customers solve data and challenges and create new solutions/capabilities for their customers.

You will develop white papers, blogs, sample dashboards, labs, and presentations to evangelize analytics and AI/ML design patterns and best practices. You will mentor and train the broader SA population within AWS, teaching them how to integrate Amazon Analytic Solutions appropriately into customer architectures.

You enjoy working with customers. You have a passion for educating, training, designing, and building cloud computing systems for some of the world's fastest growing.

As part of a Solutions Architecture team, you produce and validate reference architectures and customer adoption for AWS Analytics services including, Amazon Redshift, Amazon EMR, Amazon Data Lakes, Amazon QuickSight and Machine Learning services like Amazon Sagemaker.

Key job responsibilities
Designing Data and Analytics solutions. Work with teams at existing and potential customers to deeply understand their business and technical needs. Develop solutions that make the best use of the AWS Cloud platform and Analytics Services. Collaborate with AWS field sales, training, and support teams to ensure customer success.

Partnering with account teams, Business Development Managers and Analytics Service teams to accelerate customer adoption.

Be the voice of the customer to service engineering teams, providing product improvement feedback to AWS developers and accelerating the adoption of new features in customer deployments.

Sharing what you know by capturing best-practice knowledge from engineering and field teams, including reference architectures and patterns, with the worldwide AWS solution architect community in order to build a strong worldwide analytics and AI/ML community

Exhibiting thought leadership. Evangelize AWS Services and Analytics Solutions in the Data and Analytics domain. Share best practices through forums such as AWS blogs, whitepapers, reference architectures and public speaking events such as AWS Summit and AWS re:Invent.

About the team
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 16 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.

• Bachelor's degree in computer science, engineering, mathematics, or equivalent OR professional or military work experience
• Experience within specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics)
• Design, implementation, or consulting experience in applications and infrastructures
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience in the design and implementation of IT systems
• Experience in technology/software sales, pre-sales, or consulting
• Architecture and/or implementation experience in big data, data warehousing, data lake, operational analytics, data migration, and integration scenarios. (Amazon EMR, Hadoop, Spark, R, Presto, Hive, Amazon Redshift, Teradata, Vertica, Glue, Data Migration Services)
• Experience with modern software development practices and technologies such as agile and DevOps

• Available for travel up to 25%
• An advanced degree in computer science, MIS, engineering or related discipline
• Hands-on experience with Amazon Web Services
• Experience in Auto or in the Industrial or Finance Services sector
• Demonstrated industry leadership in the fields of Big Data processing, Database, Data Warehousing and Data Sciences
• Understanding of Artificial Intelligence / Machine Learning and advanced analytics and the application thereof in cloud-native environments
• Experience working with machine learning use case i.e. recommendation engines, prediction models, fraud detection
• Understanding of data, application, server, and network security
• Experience with Statistics, Machine Learning and Predictive Modelling

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