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What Leading a Data Team Actually Looks Like Right Now
Despite AI saturation, data leaders still face the same core challenges: proving business value, fighting tool sprawl, preventing burnout, and growing junior engineers.
What: Ben from SeattleDataGuy, who consults with dozens of data teams annually, outlines four persistent 2026 challenges: translating business needs into outcomes while navigating corporate politics, fighting dashboard and model sprawl from accessible tools like dbt and Tableau, protecting teams from burnout as data becomes a catch-all for anything technical, and growing team members while meeting immediate productivity demands.
Why it matters: AI tools haven't changed the fundamental nature of data leadership—success still depends on stakeholder management, saying no strategically, and preventing scope creep, not just technical execution.
Original article
Data leaders still face the same core challenges despite the AI hype: proving business value, managing stakeholder politics, preventing dashboard/model/tool sprawl, and saying no to low-value requests.
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