HeyJaredPipeline To Insights
Pipeline To Insights is a community-driven blog by passionate Data Engineers who share real-world experiences, technical tutorials, and personal reflections to inspire growth and continuous learning in the evolving world of data and AI.
- Indexed issues, last 90 days
- 13
- Latest publication
- Sep 29, 2026
- Audience
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- Earliest in this view
- Jul 12, 2026
Latest issues
What Has Changed in Data Engineering Interviews in 2026? (opens the original)
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A little over a year ago, I put together a 32-week series on preparing for data engineering interviews. I built the series while applying for data engineering roles, drawing on my interview experiences, research, and preparation. The series performed well at launch, and readers have kept returning to it ever since.Recently, one of P2I's subscribers asked me directly: Is that series still relevant? What’s changed since you wrote it?That question led me to take a fresh look at how data engineering
Agents in Action #8: What Makes an AI Agent Production-Ready? (opens the original)
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Over the last seven posts of the Agent in Action for data engineers series1, we built up an agent piece by piece. We gave it a tool (Part 2), connected it to an MCP server (Par
From Data Engineer to Forward Deployed Engineer (opens the original)
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Every few years in the tech world, we see new titles emerge from companies, get invented, and suddenly become a category. For example, we have seen DevSecOps Engineer1, Site Reliability Engineer2 and Analytics Enginee
Agents in Action #7: Building a Pipeline Health Monitor (opens the original)
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Back in Part 1 of this series1, we said we would eventually bring all five primitives together: tools, MCP, skills, sub-agents, and memory, and this post puts them into one working pipeline health monitor that checks table row counts, compares them with previous runs, flags anomalies, generates a useful summary, and hands the investigation over to a human. We don't use every primitive just because it exists; each
Filtering Signal from Noise in AI with Hodman Murad (opens the original)
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Do we really need to keep up with everything happening in AI? Or is the real skill knowing what is important, what isn’t, and where to spend our limited time and attention? How do we spot the signal early? How do we separate real value from hype? And once we find something promising, how do we know it’s really worth investing our time in?These are questions I’ve been thinking about recently and I was very pleased to have joined me on Pipeline to Insights to explore them.About Hodman:<a class="im
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