Senior Engineering Manager – Data and Agent Operations

What you’ll do

As Senior Engineering Manager, you’ll lead and develop our data and AI engineering organisation, ensuring we have the right people, capabilities and engineering practices to deliver high-quality digital products. You’ll work closely with other senior leaders across Data, ML, Engineering and Agentic AI to shape our technical direction and align our capabilities with Eneco’s strategic priorities.

You build, staff, mentor and lead Eneco's data delivery teams, fostering a culture of operational rigor — efficient, standardized and automated data engineering — alongside collaboration, continuous learning and innovation. You champion an operational mindset and fast learning, overseeing technical diligence, delivery focus (OTIF) and excellence, and you establish and continuously improve best practices.

You work closely with the shared Platforms organization, Data Science & Analytics, the Data & AI Office and the broader business to coordinate the delivery of high-quality data products for all of Eneco. You are the operational bridge that ensures data teams embedded in the business adopt scalable DataOps — delivering high-value insights, forecasts, predictions and optimisations that solve customer and business problems.

You’ll combine strategic leadership with a strong focus on people development and technical excellence, creating an environment where engineers can grow, collaborate and continuously improve.

Your responsibilities include

• Set the vision and direction for engineering, aligned with Eneco’s Data & AI strategy.

• Lead and develop engineering managers responsible for delivering a portfolio of data, ML, analytics and AI solutions.

• Recruit, support and mentor data engineering leads.

• Drive technical excellence and establish effective DataOps practices across teams.

• Balance autonomy within product teams with shared standards, quality and consistency across the organisation.

• Leverage agents wherever possible to automate the data work that needs doing, and lead the agentic transformation of your teams.

• Build a strong engineering community that promotes collaboration, knowledge sharing and continuous learning.

• Develop mentoring, coaching and feedback practices to support the personal and professional growth of engineers.

• Identify capability gaps and create opportunities for learning, development and career progression.

• Promote engineering best practices, including code reviews, pair programming and knowledge exchange.

Recruitment & talent management

• Define the hiring strategy and workforce needs for your domain in collaboration with other engineering leaders.