Sign inGet started
← Back to all guides

How to become a data team lead

By Nick Barth

Updated on March 6, 2024

Data has become the lifeblood of the modern business landscape, and those who can harness its power are highly sought after. Among the ranks of data professionals, the position of a data team lead stands out, requiring a unique blend of technical prowess and managerial finesse. If you're a data analyst with dreams of leading a team, this guide is for you. Delving into the nuts and bolts of the journey from analyst to team lead, we'll explore the necessary skills, experiences, and mindset shifts that pave the way for advancement.

What is a data team lead?

The first step in the journey is developing a comprehensive understanding of what a data team lead does. As an individual contributor, your focus is likely to be on analyzing data, generating insights, and supporting key business decisions. In contrast, a lead's responsibilities extend to managing workflows, guiding the development of analytical methods, and shaping the strategic direction of data projects.

Key responsibilities

A data team lead is responsible for setting the team's technical direction, ensuring that projects are completed on time and within budget, and fostering an environment where team members can grow and thrive. Understanding the needs of stakeholders and overseeing the data analysis process is crucial, all while balancing the demands of day-to-day management.

Crucial skills

To effectively manage a data team, you need a diverse skill set. Leadership, project management, and stakeholder engagement skills are as essential as your technical abilities. You must be adept at identifying and nurturing talent, advocating for resources, and fostering a collaborative team environment.

Developing technical and leadership skills

To ascend the ranks from data analyst to lead, a mindset of continuous learning is non-negotiable. This starts with expanding and updating your technical toolkit and extends to cultivating leadership competencies.

Continuous learning and upskilling

Technology in the data space is ever-evolving, so staying abreast of the latest tools and methodologies is critical. This includes platforms for data warehousing, business intelligence, and statistical analysis, as well as programming languages like Python and R. Platforms like Coursera, Udemy, and LinkedIn Learning offer a wealth of courses to help you build and refine these skills.

Communication and team management

As you step into a leadership role, your communication and team management skills will be put to the test. The ability to present complex findings in a clear and compelling manner, to empathetically manage a diverse team, and to inspire and motivate others is paramount. Consider joining public speaking groups, taking workshops on active listening, and seeking formal training in team management practices.

Relevant experience for a data team lead

Experience is the crucible in which your skills are honed and your career trajectory forged. Actively seeking out diverse experiences will set a solid foundation for your role as a lead.

Hands-on projects

Participating in a variety of projects, particularly those with cross-functional teams, will expose you to different perspectives and challenges. Look for opportunities to lead small project teams within your organization, taking responsibility for the overall success of the project.

Seeking mentorship

A mentor can be an invaluable guide, offering insights and advice that can shortcut your path to leadership. Seek out leaders in your organization who can provide mentorship and consider joining professional groups or networking events to expand your circle of advisors.

Transitioning from analyst to lead

The leap from analyst to lead represents a significant career transition that involves navigating a series of challenges. Begin by assessing the gaps between your current skill set and the skills required for a lead role.

Challenges and strategies for advancement

Common hurdles for this transition include imposter syndrome, a lack of visibility, and the need to manage former peers. Overcoming these challenges may involve seeking informal leadership roles, actively seeking feedback and focusing on results, rather than the perception of tenure.

Setting clear goals

Developing a roadmap with clear goals will help you maintain focus and momentum in your career. Identify the competencies you need to develop, the roles you need to take on, and the milestones you aim to achieve.

Showcasing leadership potential

Leadership opportunities seldom fall into your lap; you must actively pursue them. Look for ways to demonstrate your potential as a leader.

Leading by example

Exemplifying the qualities and behaviors you expect from your team will build credibility and trust. Approach your work with integrity, professionalism, and a strong work ethic to set a high bar for your team to follow.

Communicating vision and driving results

As a future leader, you must be able to articulate a vision for your team and motivate them to achieve it. This involves setting ambitious, yet achievable, goals and guiding your team to success through clear expectations and regular feedback.

Conclusion: Forging the path to data team leadership

The journey from data analyst to team lead is not a light undertaking. It requires dedication, a commitment to growth, and a strategic approach to your career development. By understanding the role, mastering the necessary skills, gaining relevant experience, and actively demonstrating your leadership potential, you can position yourself for the opportunities that lie ahead.

For those who embrace the challenge, the role of a data team lead presents a thrilling new chapter in their professional journey—a chance to shape the strategic use of data within an organization and to lead a team of talented individuals in the pursuit of common goals. For data analysts with the ambition to lead, the future is bright, and the path is clear—set your sights high, commit to the journey, and lead with purpose.

That’s it, time to try Deepnote

Get started – it’s free
Book a demo



  • Integrations
  • Pricing
  • Documentation
  • Changelog
  • Security




  • Privacy
  • Terms

© Deepnote