If you’re looking for a high-impact tech leadership opportunity, the Delivery Head-Data Engineering role stands out. This is a permanent, full-time senior-level position in the Artificial Intelligence and Data Engineering function, offering you the chance to lead innovation in GenAI strategy and enterprise data platforms. Freshers with relevant exposure to data engineering and AI/ML environments are also eligible, expanding accessibility for ambitious candidates. Salary information isn’t specified, but leadership positions at this level are typically highly competitive.

Key Responsibilities and Daily Routine

In this position, your days are dynamic and engaging. You will spearhead the definition, execution, and support of the GenAI strategy across the organisation. This includes evaluating use cases for AI and delivering measurable outcomes. Additionally, you’ll build and mature a centralized GenAI platform, ensuring the integration of cutting-edge AI models, LLM onboarding, and robust security standards.

Modernising data architecture is also a core responsibility. You’ll supervise migrations from legacy systems to modern cloud-based platforms, architect scalable ecosystems, and establish governance standards. Leading by example, you’ll drive initiatives across data ingestion, storage, and analytics, contributing to business intelligence growth.

Collaboration is paramount: you’ll interact with CXOs and department heads to translate business goals into technical solutions. Partnering with other tech and product teams is essential to deploy robust data-driven solutions.

Pros of the Role

This position lets you have a direct influence on shaping AI strategy at an enterprise level. You’ll gain exposure to modern technologies, cloud ecosystems, and innovative product development in the AI and data fields.

The multifaceted nature of the role enhances your professional growth. Working with both business and technology leaders, you set standards for best practices in AI, data security, and platform management while enabling continuous learning and upskilling.

Cons of the Role

On the flip side, being responsible for end-to-end data transformation programmes can demand long hours and the ability to quickly address evolving priorities. Complex stakeholder management and change resistance can occasionally pose hurdles.

Moreover, GenAI and data engineering fields require a commitment to staying updated with industry advances, which may feel overwhelming at times, especially for less-experienced candidates stepping in as freshers.

Verdict

Overall, this role is perfect for candidates aspiring to technology leadership with a strong interest in GenAI and enterprise data management. If you thrive in environments where innovation and collaboration intersect, applying for this position could be a transformative move for your career.