Ai/Ml Data Engineer -Remote

They need to bring on (2) AI/Client Data Engineer with data integration and Microsoft stack expertise who will specializes in designing, implementing, and optimizing data integration solutions within the context of artificial intelligence and machine learning for the CTMS.

Responsibilities:

1. Data Integration Expertise: Proficient in developing and managing data integration processes, including Extract, Transform, Load (ETL) workflows. Designing solutions to seamlessly connect and consolidate data from various sources into a unified and structured format.
2. Microsoft Stack Proficiency: In-depth knowledge and hands-on experience with Microsoft's data and cloud services. This includes expertise in Azure Data Factory for ETL, Azure SQL Database for storage, Azure Databricks for big data processing, and other relevant Azure services.
3. AI/Client Infrastructure Support: Collaborating with data scientists and AI/Client practitioners to provide the necessary data infrastructure for machine learning initiatives. Ensuring that data pipelines are optimized to support the training and deployment of machine learning models.
4. API Integration: Integrating machine learning models and AI applications into existing systems through API integration. Facilitating seamless communication and data exchange between different components of the organization's technology stack.
5. Data Governance and Compliance: Implementing data governance practices to ensure data quality, security, and compliance with regulatory standards. Utilizing Microsoft tools such as Azure Purview for data discovery, classification, and ensuring adherence to data policies.
6. Scalability and Performance Optimization: Designing data integration solutions that are scalable and can handle increasing volumes of data. Optimizing the performance of data pipelines and databases within the Microsoft Azure environment.
7. Collaboration and Communication: Working closely with cross-functional teams, including data scientists, software engineers, and business stakeholders. Understanding integration requirements and effectively communicating technical concepts to non-technical stakeholders.
8. Troubleshooting and Support: Providing support for data integration processes and infrastructure. Identifying and resolving issues, monitoring system health, and ensuring the reliability of integrated solutions.
9. Continuous Learning: Staying updated on the latest advancements in data integration, AI, and Microsoft technologies. Proactively incorporating new tools and methodologies to enhance data integration capabilities.

Qualifications:

· Proven experience as a Data Engineer with a focus on AI and Client

· Hands-on development with Microsoft stack (Azure, Azure Data Factory, SSIS, databricks) as well as Python and SQL.

· Familiarity and working knowledge of a validated system.

· Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).

· Familiarity with machine learning concepts and algorithms.

· Excellent problem-solving and communication skills.

· Ability to work independently and collaboratively in a fast-paced environment.

Skills Requirement | Success Criteria for all:

•Hyper communication and inquisitive

•Drivers with high level of self-motivation

•Extreme accountability and ownership

•Hands-on executionists vs theorists

•Critical thinking and problem-solving skills

•Experience with Validated Systems