Data Analytics Architect/Consultant, WWPS US Federal Financial ProServe
Amazon
DESCRIPTION
Do you like helping US 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 an experienced, self-driven Data Analytics Consultant. In this role, you will design and implement scalable, distributed and high-performance data architectures on AWS. You should have deep expertise and passion in working with large data sets, data visualization, building complex data modeling, ETL processes, and data warehousing concepts. 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.
Key Responsibilities include:
· Lead medium to large-scale data projects from inception to completion
· Creation and support of real-time data pipelines built on AWS technologies Amazon S3, Redshift, EMR, Glue, Athena, and Lake Formation
· Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.
· 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
· Guide clients on implementing ML solutions in their data pipeline using machine learning concepts and AWS AI/ML services like SageMaker
· Use data visualization tools like AWS QuickSight to create insightful dashboards and reports
This position requires that the candidate selected be a US Citizen.
Key job responsibilities
Key Responsibilities include:
· Lead medium to large-scale data projects from inception to completion
· Creation and support of real-time data pipelines built on AWS technologies Amazon S3, Redshift, EMR, Glue, Athena, and Lake Formation
· Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.
· 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
· Guide clients on implementing ML solutions in their data pipeline using machine learning concepts and AWS AI/ML services like SageMaker
· Use data visualization tools like AWS QuickSight to create insightful dashboards and reports
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
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Mentorship & Career Growth
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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
- Knowledge of the primary aws services (ec2, elb, rds, route53 & s3)
- Experience implementing AWS services in a variety of distributed computing environments
- Technical degree or equivalent experience
- 5+ years of relevant industry experience
- 3+ years of hands-on experience with AWS service
PREFERRED QUALIFICATIONS
- 5+ years of IT implementation experience
- Experience and technical expertise (design and implementation) in cloud computing technologies
- Experience leading the design, development and deployment of business software at scale or recent hands-on technology infrastructure, network, compute, storage, and virtualization experience
- AWS Certified Solutions Architect - Associate
- AWS Certified Data Analytics – Specialty / AWS Certified Data Engineer Associate
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.