AI Data Architect

• Creating, implementing, and maintaining cloud architecture for clients
• Migrating systems to hybrid or cloud-based solutions
• Troubleshooting and optimizing clients’ cloud infrastructure
• Working with developers to support and maintain application lifecycles
• Assisting with design and implementation of new cloud architecture that follow best practice guidelines
• Working with Project Managers and clients to provide recommendations and technology roadmaps to meet their business needs
• Actively participating in team meetings and cross-functional interactions
• Keeping team members and supervisors informed of progress and issues
• Actively contributing in client project status meetings
• Contributing to R&D projects to validate/invalidate new services offerings
• Mentoring and guiding members of the delivery team in a technical and non-technical capacity
• Remaining current with technology trends and new technologies
• Proposing latest technology usage and integration standards

• Living and breathing the “cloud-first” approach
• Having a high degree of analytical thinking capability to solve complex business problems
• Obsessively delivering amazing customer experiences
• Becoming a subject matter expert in one or more cloud platforms in 9-12 months
• Building trusting relationships with team members and collaborating departments
• Comfortable with pushing boundaries and technical limits (maintain technical aptitude and knowledge of industry)
• Always be learning

• 5+ years professional IT experience
• 2+ years professional AWS or Azure experience
• At least (1) AWS or Azure Certification (professional level)
• Programming languages like Python, R, Java, Scala etc. to build data pipelines, perform data analysis and create machine learning models.
• SQL and NoSQL databases like PostgreSQL, MySQL, MongoDB, Cassandra etc. to store and query large datasets. 
• Data modeling skills - ability to design conceptual, logical and physical data models.
• Understanding of dimensional modeling, star schemas, data warehouses. 
• ETL (Extract, Transform, Load) tools like Informatica, Talend, Pentaho etc. to integrate and move data between systems. 
• Big data frameworks like Hadoop, Spark, Kafka etc. for distributed data processing and building data lakes 
• Machine learning frameworks like Tensorflow, PyTorch, Keras, Scikit-Learn for building ML models. 
• Knowledge of data architecture patterns like lambda, kappa architecture. Ability to design scalable and flexible data pipelines. 

Compensation Disclosure:

The salary range provided is a general guideline. When extending an offer, Innovative considers factors including, but not limited to, the responsibilities of the specific role, market conditions, geographic location, as well as the candidate’s professional experience, key skills, and education/training.