Data Engineering Manager

About the role

The Data Engineering Manager will own the end‑to‑end lifecycle of AI/ML use cases, from data sourcing and pipeline creation to model deployment and monitoring. This role is critical for building a secure, scalable Data Lakehouse that powers data‑driven decision‑making across K‑Electric.

Key responsibilities

• Plan, design, and implement the enterprise Data Lakehouse, ensuring alignment with business goals and technical standards.
• Manage data governance, security policies, and compliance to maintain data integrity and controlled access.
• Monitor platform performance, usage metrics, and health, driving continuous improvement.
• Partner with business stakeholders to identify, prioritize, and deliver high‑impact AI/ML use cases such as consumer segmentation, default prediction, and theft analysis.
• Design, build, and deploy predictive models and advanced analytics solutions using modern tools.

Required profile

• Bachelor’s or Master’s degree in Information Technology, Computer Science, or a related field.
• Minimum 8 years of IT experience, including 6 years in BI analytics and data warehousing.
• At least 3 years working with Data Lakehouse technologies (e.g., SAP BDC, Databricks) and 1 year of integration experience.
• Demonstrated ability to lead teams, drive change, and make strategic decisions.

Required skills

• Python
• TensorFlow
• Databricks
• SAP BDC
• Data Lakehouse architecture
• Data pipelines and feature engineering
• Model lifecycle management
• AI/ML development

What we offer

• Opportunity to shape K‑Electric’s digital transformation journey.
• Collaborative environment with cross‑functional teams.
• Access to cutting‑edge AI/ML tools and platforms.