Offers “Amazon”

Expires soon Amazon

Associate Data Warehouse Consultant

  • Internship
  • Dallas (Dallas)
  • Marketing

Job description


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?

The Global Competency Center Professional Services team provides direct to customer, back office and packaged delivery consulting services to customers remotely. 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.

Responsibilities include:
· Employ customer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, standard methodologies, project management and risk mitigation
· Work closely with AWS Platform Service Engineering and Architecture teams to help ensure the success of project consulting engagements with customer
· Work directly with customers’ technical resources to devise and recommend solutions based on the understood requirements
· Think strategically about business, product, and technical challenges in an enterprise environment
· 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.
· Develop innovative solutions to complex business and technology problems


· Hands on experience leading large-scale global data warehousing and analytics projects
· Ability to evaluate and plan migrations to Amazon Redshift
· Experience working with large-scale full-cycle MPP enterprise data warehousing (EDW) projects
· 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
· Ability to lead client specific strategic engagements involving customer/partner teams
· Understanding of database and analytical technologies in the industry including MPP databases, Data Warehouse design, BI reporting, Dashboard development and NoSQL storage
· Desire and ability to interact with C-Level/Director level customers in IT/Business to craft their Enterprise Architecture and IT Strategies
· Strong sense of ownership, urgency, and drive.

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

Desired profile


· Bachelor’s degree, in Computer Science, Engineering, Mathematics or a related field or equivalent professional or military experience
· Experience of IT platform implementation in a technical and analytical role
· 1+ years of experience of development and/or DBA experience in Relational Database Management Systems (RDBMS)
· 1+ years of hands-on experience in implementation and performance tuning MPP databases (Teradata, Vertica, Netezza, Greenplum)
· Experience designing database environments, analyzing production deployments, and making recommendations to optimize performance

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