Data Architect (AWS)

Job Description
Publicis Sapient is looking for a Data Architect to join our team of bright thinkers and
doers. You will team with top-notch technologists to enable real business outcomes for
our enterprise clients by translating their needs into transformative solutions that provide
valuable insight. Working with the latest data technologies in the industry, you will be
instrumental in helping the world’s most established brands evolve for a more digital
future.
Your Impact:
• Play a key role in delivering data-driven interactive experiences to our clients
• Work closely with our clients in understanding their needs and translating
  them to technology solutions
• Provide expertise as a technical resource to solve complex business issues
   that translate into data integration and database systems designs
• Problem solving to resolve issues and remove barriers throughout the
   lifecycle of client engagements
• Ensuring all deliverables are high quality by setting development standards,
   adhering to the standards and participating in code reviews
• Participate in integrated validation and analysis sessions of components and
  subsystems on production servers
• Mentor, support and manage team members
Your Skills & Experience:
• Demonstrable experience in enterprise level data platforms involving
  implementation of end to end data pipelines
• Good communication and willingness to work as a team
• Hands-on experience with at least one of the leading public cloud data
   platforms (Amazon Web Services)
• Experience with column-oriented database technologies (i.e. Big Query,
   Redshift, Vertica), NoSQL database technologies (i.e. DynamoDB, BigTable,
   Cosmos DB, etc.) and traditional database systems (i.e. SQL Server, Oracle,
   MySQL)
• Experience in architecting data pipelines and solutions for both streaming and
   batch integrations using tools/frameworks like Glue ETL, Lambda, Google
   Cloud DataFlow, Azure Data Factory, Spark, Spark Streaming, etc.
• Ability to handle multiple responsibilities simultaneously in leadership and
   contributing to tasks “hands-on”
• Understanding of data modeling, warehouse design and fact/dimension
   concepts