Data & AI Enablement Manager / Assistant Manager
Head of Data and AI Enablement or equivalent senior data leader
The Data & AI Enablement Manager is responsible for accelerating the organization’s data and AI initiatives by building scalable solutions, streamlining data operations, and enabling business teams to experiment and innovate efficiently.
This role bridges technology and business functions by developing low-code applications, data pipelines, and automation tools that support analytics and AI use cases in a controlled and governed environment.
Design and deliver low-code and data engineering solutions that enable business functions to prototype AI and analytics use cases efficiently.
Validate and optimize AI models and data products to ensure accuracy, quality, and readiness before production deployment.
Build and maintain data pipelines, APIs, and automation tools that support reusable and scalable analytics capabilities.
Collaborate closely with IT, data governance, and business stakeholders to align technical delivery with organizational standards and priorities.
Implement and monitor data quality controls, resolve issues, and continuously improve data processes.
Provide technical guidance and mentorship to team members and junior engineers in the data enablement function.
Document best practices, process flows, and reference architectures to support platform standardization and knowledge sharing.
Bachelor’s degree or higher in Computer Science, Data Engineering, Information Systems, or related field.
5 or more years of experience in data engineering, analytics, or AI solution development within a corporate or enterprise environment.
Hands-on expertise in Python, SQL, and data pipeline orchestration tools (e.g., Airflow, Prefect, Azure Data Factory, etc.).
Experience with low-code or no-code platforms (such as Power Platform, Dataiku, KNIME, or Alteryx).
Familiarity with API development, CI/CD processes, and cloud data architectures (AWS, Azure, GCP).
Strong understanding of data governance, model validation, and quality frameworks.
Excellent problem-solving skills, attention to detail, and ability to communicate technical concepts to non-technical stakeholders.
Opportunity to shape the data and AI enablement capabilities of a growing enterprise.
Exposure to cutting-edge technologies and cross-functional innovation projects.
Collaborative, fast-paced environment that values experimentation and continuous learning.