Job Summary

The AI & Data Engineering Manager at CCBVL have demonstrated experience in data infrastructure and data architecture skills, a proven track record of leading and scaling BI teams, demonstrated experience in operational skills to drive efficiency and speed, project management leadership, and a comprehensive vision for how data can proactively improve companies.

Key Responsibilities

• Proactively drive the vision for BI and Data and AI across a product vertical and define and execute on a plan to achieve that vision.
• Define the processes needed to achieve operational efficiency in all areas, including project management and system reliability.
• Build a high-quality BI and AIOps team and design the team to scale.
• Build cross-functional relationships with Business teams, Data Scientists, Data Engineers and Regional and global Data & AI COE teams to understand data needs and deliver on those needs.
• Drive the design, building, and launching of new data models and data pipelines in production.
• Drive data quality across the product vertical and related business areas.
• Manage the delivery of high impact dashboards and data visualizations.
• Define and manage SLA’s for all data sets and processes running in production.
Data & AI Solution Design
• Lead the design of scalable data pipelines, data lakes, and AI platforms
• Ensure all solutions align with regulatory and data governance standards
• Create blueprints, documentation, and patterns for secure and governed AI and data infrastructure
• Drive architecture that supports rapid delivery while maintaining data quality and reliability
Value-Driven AI Deployment
• Lead the design and implementation of scalable AI/ML solutions including predictive models, process automation, generative AI, and advanced analytics, with a clear focus on delivering tangible business outcomes.

Requirements

• Bachelor’s degree in computer science, Data Science, Engineering, or related field.
• Certifications in Databricks, Power BI, or cloud platforms are a plus.
• 3+ years of experience in data engineering or AI/ML development.
• Hands-on experience with Databricks, Power BI, and enterprise system integration.
• Expertise in LLMs, MLOps, GenAI, cloud architecture, and data infrastructure
• Excellent written and oral English and Local Language.
• Strong understanding of data architecture, ETL/ELT processes
• Proficiency in Python, SQL, Spark.
• Familiarity with AI/ML frameworks (Azure AI, PyTorch).
• Strong analytical and problem-solving skills.
• Ability to work independently and in teams.