{"podcast":{"title":"Data Science Tech Brief By HackerNoon","slug":"data-science-tech-brief-by-hackernoon-6367564","podcast_index_feed_id":6367564,"rss_url":"https://feeds.transistor.fm/data-science-tech-brief-by-hackernoon","website_url":null,"image_url":"https://img.transistorcdn.com/PRg81mb1bHdu71bs3zSzRC6oEjt9WcIHjS2ba3uMWCY/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjY4LzE2ODM1/ODI1ODUtYXJ0d29y/ay5qcGc.jpg","author":"HackerNoon","episode_count":100,"summary":"Learn the latest data science updates in the tech world.","last_synced_at":"2026-06-18T06:17:56.540839+00:00","page_url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564"},"episode":{"title":"Data Engineering Teams Need a Different Version of Agile","slug":"data-engineering-teams-need-a-different-version-of-agile","published_at":"2026-05-28T16:00:43+00:00","page_url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564/data-engineering-teams-need-a-different-version-of-agile","show_page_url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564","url":"https://share.transistor.fm/s/8c8d114a","audio_url":"https://media.transistor.fm/8c8d114a/388f479a.mp3","summary":"This story was originally published on HackerNoon at: https://hackernoon.com/data-engineering-teams-need-a-different-version-of-agile . This article explores which Agile practices actually help data engineering teams and which ceremonies often become operational overhead. Check more stories related to data-science at: https://hackernoon.com/c/data-science . You can also check exclusive content about #data-governance , #agile-data-engineering , #data-pipelines , #pipeline-monitoring , #backlog-management , #engineering-management , #pipeline-validation , #data-operations , and more. This story was written by: @kuladeepsandra . Learn more about this writer by checking @kuladeepsandra's about page, and for more stories, please visit hackernoon.com . Agile is useful for data engineering teams when it creates visibility, reduces context switching, and helps teams manage uncertainty. A visible backlog, regular delivery rhythm, and meaningful retrospectives usually help. Story point velocity tracking and status-report standups often become ceremony. The goal is not to “do Agile.” The goal is to create enough structure to prevent shortcuts, surface blockers early, and deliver reliable data work.","meta_description":"This story was originally published on HackerNoon at: https://hackernoon.com/data-engineering-teams-need-a-different-version-of-agile . This article explo…","key_points":[],"chapters":[],"topics":[],"duration_seconds":765,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/data-science-tech-brief-by-hackernoon-6367564/episodes/data-engineering-teams-need-a-different-version-of-agile/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/data-science-tech-brief-by-hackernoon-6367564/data-engineering-teams-need-a-different-version-of-agile.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}