Internship: Sr Data Architect - Data Warehouse & Mpp - Nationwide Opportunities
Internship - Amazon
Are you a Data Analytics specialist? Do you have Data Warehousing, Hadoop/Data Lake experience? Do you like to solve the most complex and high scale (billions + records) data challenges in the world today? Do you like to work on-site in a variety of business environments, leading teams through high impact projects that use the newest data analytic technologies? Would you like a career path that enables you to progress with the rapid adoption of cloud computing?
This role will specifically focus on large scale data warehousing and data warehouse modernization. The role is to help our customers and partners to eliminate technical and economic constraints from their legacy data warehouses and help them to leverage their data to develop business insights. Our consultants will develop, deliver and implement data warehouse projects that help our customers help our customers leverage their data to develop business insights. These professional services engagements will focus on customer solutions such as data warehousing, business intelligence and advanced analytics.
· Expertise - Collaborate with AWS field sales, pre-sales, training and support teams to help partners and customers learn and use AWS services such as Redshift, Database Migration Service, Glue, S3, and Schema Conversion Tool.
· Solution - Deliver on-site technical engagements with partners and customers. This includes participating in pre-sales on-site visits, understanding customer requirements, contributing to internal Area of Depth (AoD) programs, authoring AWS Data Analytics best practice blogs/whitepaper and creating packaged data service offerings.
· Delivery - Engagements include short on-site projects to assess and optimize customer’s Amazon Redshift implementations and helping customers to migrate from their existing on-premises data warehouses using other databases to Amazon Redshift.
· Innovate - Engaging with the customer’s business and technology stakeholders to create a compelling vision of a data-driven enterprise in their environment
This is a customer facing role. You will be required to travel to client locations and deliver professional services when needed.
· Masters or PhD in Computer Science, Physics, Engineering or Math
· Ability to evaluate and plan migrations to Amazon Redshift
· One of the AWS Associate level certifications or AWS Certified Cloud Practitioner.
· Extensive hands on experience in leading large-scale full-cycle MPP enterprise data warehousing (EDW) projects
· Extensive hands on experience in data warehousing design, tuning and ETL/ELT process development
· Excellent SQL and strong hands-on scripting (bash, perl or python) ability
· Experience implementing AWS services in a variety of distributed computing, enterprise environments
· Understanding of database and analytical technologies in the industry including MPP databases, Data Warehouse design, BI reporting, Dashboard development and NoSQL storage
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:
· Bachelor’s degree in Computer Science, Engineering, Mathematics or a related field or equivalent professional or military experience
· 8+ years of experience of IT platform implementation in a technical role
· 8+ years of development and/oar DBA experience in Relational Database Management Systems (RDBMS)
· 5+ years of hands-on experience in implementation and performance tuning MPP databases (Teradata, Vertica, Netezza, Greenplum)
· Experience with prioritization of projects that mitigate trade-offs
· Experience in analyzing Data Warehouses such as Teradata, Netezza, Oracle, etc. or Greenplum etc.
· Experience designing database environments, analyzing production deployments, and making recommendations to optimize performance