The execution of increments in data programs, particularly within the Scaled Agile Framework (SAFe), presents unique challenges and opportunities. This paper explores real-world experiences and lessons learned from implementing Program Increments (PIs) in a data program, drawing on insights from the role of a Release Train Engineer or Agile Practitioner. Key challenges include aligning diverse teams on shared objectives, managing dependencies across distributed teams, and addressing technical complexities inherent in data platforms. The study identifies critical success factors such as robust planning, effective stakeholder engagement, and the application of Agile and DevOps practices to enhance increment execution. Through a case-study approach, the paper highlights the importance of fostering a culture of collaboration, continuous improvement, and adaptive governance to mitigate risks and ensure alignment. The findings provide actionable insights for practitioners and organizations seeking to optimize increment execution in data programs, contributing to the broader body of knowledge on scaling Agile frameworks for complex technological initiatives.