Uploaded June 2026 | Updated September 2026, 1 week ago
Data Engineer's survival guide: writing pipelines that don't break at 3 AM (Indrasena Manga) - PyTexas 2026
Let's say you are notified that a critical pipeline failed because a source file contained a string in a column that was supposed to be an integer.
Data Engineering doesn't have to be a constant cycle of firefighting. By borrowing battle tested practices from traditional software engineering like strict type hinting, robust unit testing, and defensive design, we can build pipelines that are resilient by default. This talk is a survival guide for the modern Data Engineer.
We will move beyond scripting and explore how to use standard Python tools (like Pydantic, pytest, and logging) to catch dirty data and logic errors in CI/CD, long before they wake you up.
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🎤 Speaker: Indrasena Manga
Indrasena Manga, a Senior Data Engineer at AXS.com (Texas, USA) with expertise in AI/ML systems, real-time data streaming, and large-scale data engineering. I've authored 10+ Scopus and IEEE indexed research papers, served as a Session Chair & Guest Speaker at IEEE ComputingCon-2025, served as a Session chair for GCAT-2025, and completed 30+ peer reviews for Elsevier, Springer, and IEEE. I'm a provisional patent holder (USPTO) for an AI-driven disaster relief system and an active member of IEEE, ACM (SIGAI, SIGKDD), and SCRS.
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🔗 Conference Info
pytexas.org/2026
📬 Subscribe
pytexas.org/newsletter
Data Engineer's survival guide: writing pipelines that don't break at 3 AM (Indrasena Manga) - PyTexas 2026
Let's say you are notified that a critical pipeline failed because a source file contained a string in a column that was supposed to be an integer.
Data Engineering doesn't have to be a constant cycle of firefighting. By borrowing battle tested practices from traditional software engineering like strict type hinting, robust unit testing, and defensive design, we can build pipelines that are resilient by default. This talk is a survival guide for the modern Data Engineer.
We will move beyond scripting and explore how to use standard Python tools (like Pydantic, pytest, and logging) to catch dirty data and logic errors in CI/CD, long before they wake you up.
---
🎤 Speaker: Indrasena Manga
Indrasena Manga, a Senior Data Engineer at AXS.com (Texas, USA) with expertise in AI/ML systems, real-time data streaming, and large-scale data engineering. I've authored 10+ Scopus and IEEE indexed research papers, served as a Session Chair & Guest Speaker at IEEE ComputingCon-2025, served as a Session chair for GCAT-2025, and completed 30+ peer reviews for Elsevier, Springer, and IEEE. I'm a provisional patent holder (USPTO) for an AI-driven disaster relief system and an active member of IEEE, ACM (SIGAI, SIGKDD), and SCRS.
---
🔗 Conference Info
pytexas.org/2026
📬 Subscribe
pytexas.org/newsletter
