Stop identifying with your job title! It’s a trap that will keep your poor You aren’t a data engineer or a product manager. You’re a human capable of adapting and learning so much. When I was working at Airbnb, they were like, you’re one of the best data engineers, Zach. We want you to become a principal data engineer! The glory of being a principal engineer in big tech. Wow! And I drank the Koolaid fully from 2016 to 2023. But so much sugar ultimately made my stomach sick and I realized my life was more than SQL, Scala, Spark and Airflow. I irrationally left a $600k data engineering job for a $0 content creator business. I was destined to be an internet clown and educator. I traded SQL for shitposting. I traded Spark for sales. I traded Scala for scaling my business. I traded Airflow for art. And now this absolutely absurd decision in 2023 is looking better and better as technical skills continue to get undermined by AI. Give yourself to reinvent yourself! Give yourself permission to change jobs! You’re a multi potential human Intelligence is the ability to adapt to change!

Kevin O'Leary is destroying my home town in Utah for the sake of corporate greed! He’s pushing to build a data center near my hometown in Utah that uses 558 MILLION gallons of water every single year. Utah is the second driest state in the US and DOES NOT HAVE the water to support this data center. This plan will rapidly dry up the Great Salt Lake and we will have a very similar catastrophe like what happened to the Aral Sea in Kazakhstan At the bottom of the Great Salt Lake is tons of arsenic that will be exposed if this project gets approved! The protests a few months back caused him to decline building the data center. But he REFILED to build it. We as Utahns MUST FIGHT BACK! If you want to be part of the protest. His water application number is a55167 and you can submit a formal protest for $15. If you’re an Utah resident, I will send you $15 to submit the formal complaint (just send me a screenshot of your submitted application in a LinkedIn DM and your Venmo handle) You can submit your formal complaint here: waterrights.utah.gov/protest… Get out of Utah and go back to Canada, Kevin! Your data center that will poison the children in my home town for generations! Please unfollow Kevin. He will stomp on Utah children to get as much profit as he possible can!

Turning a vibe-coded data pipeline into production-grade software requires thinking about 100s of different engineering concepts! AI can generate an ETL pipeline in minutes. But getting that pipeline to process billions of records reliably, maintain data quality, and recover from failures? That’s a completely different animal! Here’s what vibe coders building data pipelines need to learn: 1. Data Ingestion & Extraction * Batch vs. streaming ingestion * Change Data Capture (CDC) * Full vs. incremental loads * API rate limiting * Schema inference * Data serialization * Idempotent ingestion * Late-arriving data 2. Data Modeling & Storage * Star schemas * Snowflake schemas * Slowly Changing Dimensions (SCDs) * Fact and dimension tables * Data normalization * Partitioning * Clustering * File compaction * Columnar storage * Data lakehouse architectures 3. Distributed Data Processing * Data shuffling * Data skew * Broadcast joins * Sort-merge joins * Predicate pushdown * Partition pruning * Parallelism * Memory management * Adaptive query execution 4. Orchestration & Reliability * DAG orchestration * Task dependencies * Retries * Exponential backoff * Idempotency * Backfills * SLAs * Data freshness * Failure recovery * Workflow scheduling 5. Streaming & Real-Time Data * Event time vs. processing time * Watermarks * Windowing * Exactly-once vs. at-least-once processing * Event deduplication * Out-of-order events * Checkpointing * State management * Kafka partitions * Backpressure 6. Data Quality & Governance * Data contracts * Schema evolution * Schema enforcement * Null handling * Duplicate detection * Referential integrity * Data validation * Data lineage * PII handling * Access controls * GDPR compliance 7. Performance & Cost Optimization * Warehouse sizing * Autoscaling * Query caching * Materialized views * Incremental materialization * Storage optimization * Compute optimization * Cost attribution * Concurrency management * Query profiling 8. Deployment & Observability * CI/CD for data pipelines * Infrastructure as Code * Environment isolation * Unit testing * Integration testing * Data reconciliation * Pipeline monitoring * Data quality alerts * Freshness monitoring AI has reduced the cost of writing data transformations! But it hasn’t eliminated the complexity of running data pipelines at scale. You can easily vibe code your way to a pipeline that works on 10,000 rows. But when that pipeline needs to process 10 billion rows, handle schema changes, recover from partial failures, or guarantee downstream data correctness. You’re basically cooked！ The future isn’t data engineers vs. vibe coders. It’s data engineers who understand distributed systems, data architecture, and production reliability AND know how to leverage AI. Writing SQL and Python is getting cheaper. Data engineering judgment is becoming more valuable！ What would you add to the list? Inspired by Natalie L.

Job hopping in 2026 isn’t like what it was in 2021! Oprah isn’t out there giving everybody jobs like during the zero interest rate world That being said, job hopping is still one of the best ways to get promoted and raises - the new company judges you based on your stories and potential - the current company judges you based on your results Sometimes being too results focused can cause management to be too conservative in their promotion criteria. Managers all have a story of promoting someone too early and regretting it but they don’t have as many stories of regret where they make an engineer wait. If you believe you’re at the next level, the best way to test that is by going out into the market and trying! But in a layoff heavy environment, the new hires are often the ones most likely to get laid off. So it’s not as clear cut as it was in 2021. I’m doing a one hour webinar with Prasad Rao on how to determine if job hopping is right for you or if getting promoted within your company is better! You can join here: bigtechcareers.techexpert.io…

The layoffs from Netflix are really hard to see! I’ve always held Netflix to a higher standard. They keep teams smaller intentionally. They have high standards of their employees and let go people who truly aren’t A players. Seeing them let go 1,000 A players today shows me that Netflix is in a tough spot. Talent is what has made Netflix great! If you were affected by these layoffs, we can get you 50% off the DataExpert platform so you can upskill and maybe get you a job at Anthropic or OpenAI like Mike Chuang (one of our previous students). Send me a DM and we can schedule a free 1:1 so I can gas you up and show you these layoffs will be the greatest thing to ever happen to you!