Senior Engineering Manager - Data and Agent Operations

Details

Lead Eneco’s Data & AI Engineering organisation by shaping engineering strategy, developing engineering leaders and building high-performing teams that accelerate the company’s digital transformation. The role focuses on engineering excellence at scale through standardised and automated DataOps practices and the adoption of Agentic AI to improve efficiency, quality and delivery.

Responsibilities

Leadership and strategy

• Set the vision and direction for engineering in alignment with Eneco’s Data & AI strategy.
• Lead and develop engineering managers responsible for data, ML, analytics and AI solutions.
• Recruit, support and mentor data engineering leads.
• Drive technical excellence and establish effective DataOps practices across teams.
• Balance product-team autonomy with shared standards, quality and consistency.
• Lead the agentic transformation of data engineering teams and automate data work wherever possible.

People development and engineering excellence

• Build an engineering community focused on collaboration, knowledge sharing and continuous learning.
• Develop mentoring, coaching and feedback practices.
• 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 and talent management

• Define hiring strategy and workforce needs in collaboration with other engineering leaders.
• Shape roles, job descriptions and recruitment processes with Talent Acquisition and fellow engineering leaders.
• Ensure the required talent and capabilities are available for current and future business needs.
• Align talent development with business priorities in collaboration with Group Product Managers and other leaders.

Stakeholder management and collaboration

• Partner with the business to execute the enterprise data and AI strategy and data technology vision.
• Build relationships with senior business and technology stakeholders.
• Contribute to strategic decisions across the TECH organisation, connecting data, ML, AI and engineering capabilities.
• Coordinate with Platforms, Data Science & Analytics, the Data & AI Office and the broader business to deliver high-quality data products.

Requirements

• Strong experience leading multiple data engineering or ML teams in an enterprise setting.
• Proven experience delivering data engineering and ML solutions and aligning technical work with business goals.
• Fluency with agentic ways of working and a willingness to automate repetitive, error-prone data work.
• Extensive experience in a senior engineering leadership role within data, AI or technology platforms.
• Strong expertise in data engineering, including modern enterprise data management, data integration and distributed data processing.
• Familiarity with ML engineering, AI systems and Agentic AI model lifecycles is an advantage.
• Solid engineering background spanning architecture, development and data operations.
• Experience with cloud technologies; knowledge of Databricks, Snowflake and Azure is a plus.
• Excellent communication and stakeholder management skills, including the ability to influence senior leaders.
• Ability to navigate ambiguity, balance competing priorities and adapt to different situations.
• Proactive mindset with a focus on continuous improvement.
• Interest in coaching people, developing talent and building an inclusive engineering culture.

Benefits

• Gross annual salary of €112,000–€180,000, including FlexBudget and 8% holiday allowance; a bonus or collective profit sharing may apply depending on the role.
• FlexBudget that can be paid out, used to purchase additional holiday days or saved.
• Personal and professional development support.
• Hybrid working: 40% in the office, 40% from home and 20% flexibly.
• With manager approval, the possibility to work abroad in approved countries for up to three weeks per year, with a maximum of two consecutive weeks.
• Flexible working hours and the option to work from home where the role allows.

The role is part of Eneco’s TECH organisation and dedicated data department, working with colleagues across Data, ML, Engineering and Product to support digital innovation and the energy transition.