Data Leadership Roles: Balancing Technical Skills & Strategic Vision

Are you looking for your next position in the data leadership space? Perhaps as a Head of Data or a Chief Data Officer?

If so, you might have noticed that in the ‘requirements’ section of many job adverts, there’s still a need to be ‘proficient in Python or SQL’ and a preference for candidates to be ‘hands-on’ with coding. This can be frustrating for many, especially for those who have progressed in their careers and moved away from these responsibilities.

At Orbition Group, we engage in daily conversations with Data & Analytics leaders—whether they’re looking for their next career move or just chatting about market trends. One recurring theme is the frustration over the expectation for data leaders to remain technically involved. In most industries, as you climb the ladder, you tend to step away from hands-on tasks, whether it’s ‘building a pipeline’ or ‘designing a data lake.’ So why, in Data & Analytics, are so many employers still looking for technical skills at the leadership level?

Why Do Technical Skills Matter?

It’s true that having some level of technical understanding is important for data leadership roles. Leaders often support teams of Data Engineers, Architects, Analysts, and others, so understanding the tools and technologies they use is valuable. However, relying heavily on a senior leader’s technical expertise might not always be the best approach.

Technology is evolving rapidly—tools, programming languages, and platforms like Databricks or Snowflake change year on year. Many data leaders do keep up with these trends to inform their data strategy, but as they develop in their careers, the practical side of coding often becomes less familiar. Broad knowledge is more valuable in these leadership roles than deep technical expertise, especially when the organisation can afford to hire technical specialists.

The Role of a Data Leader: Vision Over Execution

Moving into a data leadership position typically involves stepping into a more strategic role. These leaders need to set the vision for how data is used across the organisation, aligning data strategies with business goals. Their focus shifts from day-to-day technical tasks to fostering a data-driven culture, influencing stakeholders at all levels, and managing resistance to change.

In smaller organisations or companies early in their data journey, it’s understandable that leadership roles might still require technical skills. These businesses may be searching for a ‘unicorn’—someone who can handle both strategy and execution. But as businesses mature and their senior leadership teams become more serious about leveraging data for business outcomes, they’ll likely shift away from this hybrid approach.

Navigating the Increasing Demand for Technical Expertise

The growing demand for technical skills in senior roles could stem from the complexity of modern data ecosystems. The rise of Artificial Intelligence, Machine Learning, and data products has added new layers of complexity that data leaders need to understand when building their strategies.

While CDOs were once primarily focused on data governance and quality, their role now encompasses innovation, product development, and driving new business opportunities. This shift has placed a premium on technical fluency, as leaders need to effectively communicate with technical teams and other business units.

Conclusion: Striking the Right Balance

In summary, the expanding technical landscape in Data & Analytics means that leadership roles must balance technical literacy with strategic vision. Yes, technical knowledge is an important part of successful data leadership, but organisations must remember that many senior leaders have moved away from hands-on technical tasks.

To attract the perfect candidate, it may be time to reconsider whether proficiency in Python or SQL is a necessity for a leadership role, or if the focus should be on broader strategic capabilities that drive business outcomes.

Natalia is a highly skilled senior talent partner. With a passion for identifying top talent and a strong commitment to customer service, she has established herself as a valuable resource to both clients and candidates in the data & analytics industry.

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