Description

Do you like helping U.S.Federal agencies implement innovative cloud computing solutions and solve technical problems? Would you like to do this using the latest cloud computing technologies? Do you have a knack for helping these groups understand application architectures and integration approaches, and the consultative and leadership skills to launch a project on a trajectory to success? Amazon Web Services (AWS) Professional Services engage in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about strong success for the Customer. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.

We are looking for experienced, self-driven Data Engineer. In this role, you will be building complex data engineering and business intelligence applications using AWS big data stack. You should have deep expertise and passion in working with large data sets, data visualization, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You should have excellent business acumen and communication skills to be able to work with business owners to develop and define key business questions and requirements. You will provide guidance and support for other engineers with industry best practices and direction. AWS has culture of data-driven decision-making, and demands timely, accurate, and actionable business insights.

This position requires that the candidate selected be a US Citizen.

Key job responsibilities

• Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.

• Develop and manage ETLs to source data from various financial, AWS networking and operational systems and create unified data model for analytics and reporting.

• Creation and support of real-time data pipelines built on AWS technologies including EMR, Glue, Redshift/Spectrum and Athena.

• Collaborate with other Engineering teams, Product/Finance Managers/Analysts to implement advanced analytics algorithms that exploit our rich datasets for financial model development, statistical analysis, prediction, etc.

• Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency.

• Use business intelligence and visualization software (e.g., QuickSight) to develop dashboards those are used by senior leadership.

• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.

• Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.

• Manage numerous requests concurrently and strategically, prioritizing when necessary

• Partner/collaborate across teams/roles to deliver results.

• Mentor other engineers, influence positively team culture, and help grow the team.

About the team

About the Team

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.

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

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 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 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Basic Qualifications

• 3+ years of data engineering experience

• Experience with data modeling, warehousing and building ETL pipelines

• Experience with SQL

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

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

• Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent

• Prior experience in programming using Python

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.