We study the determinants of lifetime earnings (LE) inequality in the U.S. by focusing on job ladder dynamics and on-the-job learning as sources of wage growth. Using administrative data, we document that i) lower LE workers change jobs more often, which is mainly driven by nonemployment; ii) average annual earnings growth for job stayers is similar, around 2% in the bottom two-thirds of the LE distribution, whereas for job switchers it rises with LE; iii) top LE workers enjoy around 10% average earnings growth regardless of job switching. We estimate a job ladder model with on-the-job learning featuring a rich set of worker types and firm heterogeneity. We find that the vast differences across worker types in job ladder risk—job loss, job finding, and contact rates—account for 80% of wage growth differences among workers below median LE. Above the median, almost all lifetime wage growth differences are a result of Pareto-distributed learning ability. We conclude that different economic forces are driving the inequality in different parts of the LE distribution.