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AI Engineering vs. Data Engineering: The $534K Question

An analysis of the shifting market landscape for data professionals, weighing AI engineering opportunities against stable data engineering paths for new graduates and upskillers.

#AI engineering#career strategy#Data Engineering...

AI Integration

The Black Box Beneath: Why AI Initiatives Stall at the C++ Struct Barrier

The brutal reality of extracting training data from undocumented legacy infrastructure where critical business logic lives in opaque C++ and Perl glue code.

#AI Integration#C++#Data Engineering...

AI Agents

The November 2025 Inflection: How Data Teams Actually Use AI Agents Without Burning Their Codebase

An examination of real-world generative AI adoption patterns in data science, moving from chatbot assistance to autonomous agent workflows.

#AI Agents#Claude Code#data science...

cdc

From Hourly to Real-Time: Architecting Event-Driven Pipelines with CDC

Case study analysis of using Change Data Capture (CDC) to eliminate batch latency bottlenecks at scale, inspired by Pinterest’s recent architecture updates.

#cdc#event-driven#kafka...

business logic

The Business Logic Holy War: Why Your ‘Single Source of Truth’ Is Already Compromised

The debate over where business logic belongs in modern data architectures reveals an uncomfortable truth: the ideal of centralizing everything in the transformation layer collides with messy reality. Here’s what actually works.

#business logic#data architecture#Data Engineering...

duckdb

The Rise of DuckDB and Polars in Modern Data Engineering Pipelines

Why data engineers are abandoning Spark clusters for lightweight tools that run on laptops, and why your ‘big data’ pipeline probably doesn’t need to be big at all.

#duckdb#etl#polars

constraints

Database Constraints: The Features You’re Too Scared to Use (But Shouldn’t Be)

EXCLUDE and CHECK constraints sit in PostgreSQL like power tools gathering dust. Are they underused gems or overengineered footguns? The answer depends on how much you trust your data to outlive your code.

#constraints#data-integrity#database-design...

binary-encoding

The Great JSON Resurrection: Binary Encoding’s Revenge on Performance Critics

Relational purists declared JSON dead in production databases. Then binary encoding arrived with 2,346x speedups and made them eat their words. Here’s how modern systems actually make semi-structured data fly.

#binary-encoding#database-performance#json...

careers

The Data Science Jobs AI Is Already Killing (And the Ones It Can’t Touch)

How data science educators and professionals should address AI-driven job market changes with students entering the field.

#careers

ai evaluation

The Benchmark Is Lying: Qwen Team Exposes Massive Flaws in AI’s Most Trusted Tests

GPQA and HLE, benchmarks that determine which AI models lead the pack, are fundamentally broken. The Qwen team’s systematic verification reveals incorrect answers, ambiguous problems, and systematic errors that artificially deflate model scores by up to 40%.

#ai evaluation#data quality#GPQA...

database-design

The Multi-Tenant Database Dilemma: Why PostgreSQL’s Two Best Features Are Trying to Kill Your Healthcare SaaS

Row-level security promises scalability but hides performance traps. Schema-per-tenant offers bulletproof isolation but becomes an operational hydra at 100+ tenants. In healthcare SaaS, choosing wrong means data breaches or bankruptcy.

#database-design#healthcare#multi-tenant...

API design

The Cold Storage Lie: Why Your API Might Be Fine Querying S3 Directly

Fintech systems are hemorrhaging money on cold data storage. The conventional wisdom says you need Redshift or Athena, but the math, and the architecture, tells a more complicated story.

#API design#cold storage#Fintech...