Data Engineering Architect- Aws Cloud

Job Description
Publicis Sapient is looking for a Data Architect -AWS Cloud 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:
- 8+ years of 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 platform- AWS (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