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

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

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.