A Diwali lunch reminded us that reliable data starts with people who trust each other
Last week we did something simple. We closed our laptops, left the dashboards and tickets behind, and sat down together for a Diwali team lunch.
There was good food. There were long conversations that had nothing to do with schemas or jobs. There was laughter about the bugs that once kept us up at night.
Somewhere between the second plate and the chai, a quiet thought came back. Building a business is as much about the people you work with as the work itself. The same is true for every data platform in the world.
From the outside, data engineering looks like code. Pipelines, tables, clusters, queries.
But think about the last real incident you fixed. A column changed meaning. A source team renamed a field. A dashboard showed the wrong number for two weeks and nobody said anything.
None of these were Spark problems. They were conversation problems. Someone knew something that someone else needed to know.
Great data systems are built by teams who talk to each other. Fragile ones are built by people working alone.
The fastest outage recovery we have seen did not come from the smartest engineer. It came from someone who said early, "I changed this yesterday. Can we look together?"
That sentence only happens when people feel safe. When mistakes are punished, people hide them, and problems grow quietly in your tables.
A ticket that says "build a revenue table" tells you almost nothing. A ten minute talk with the finance analyst tells you what revenue actually means, which refunds count, and which dates matter.
The best tables are not written from tickets. They are written after conversations.
Data never sleeps, but people must. Teams that rotate on-call fairly, write clear runbooks, and celebrate together stay longer and build better.
A festival lunch is not a break from the work. It is part of how good work keeps happening.
flowchart LR
A[People who trust each other] --> B[Honest conversations]
B --> C[Shared context]
C --> D[Clear tables and contracts]
D --> E[Reliable data and AI]
E --> F[Better decisions for everyone]Here is a small habit that turns team knowledge into something lasting. In Databricks Free Edition, open a SQL editor and run this.
CREATE TABLE IF NOT EXISTS workspace.default.festive_orders (
order_id BIGINT COMMENT 'Unique order number from the shop system',
order_date DATE COMMENT 'Date the customer placed the order',
amount DECIMAL(10,2) COMMENT 'Order value after discounts, before tax'
)
COMMENT 'Daily orders during festival season. Owned by the data team. Ask in the team channel before changing columns.';
ALTER TABLE workspace.default.festive_orders
SET TBLPROPERTIES ('owner_team' = 'data-engineering', 'refresh' = 'daily');
DESCRIBE TABLE EXTENDED workspace.default.festive_orders;Look at the output. Every column now explains itself. The table says who owns it and how often it changes.
The next person who opens this table, maybe a new teammate, maybe an AI agent, will not have to guess. That is teamwork written into the data itself.
Whether you work in Bengaluru, Chicago, London, Lagos or São Paulo, the pattern is the same. The tools change every year. The need for people who listen, explain and support each other does not.
As AI takes on more of the routine work, the human parts of our job grow more valuable. Understanding the business. Asking the right question. Helping a teammate who is stuck.
These are the skills that no model can replace.
Diwali is the festival of lights. It celebrates light over darkness and knowledge over confusion.
That feels close to what we do. Every clean table, every clear explanation, every shared lesson pushes back a little darkness.
To every data engineer, analyst, scientist and learner around the world, we wish you a bright and peaceful Diwali. May your pipelines run green, your data stay honest, and your teams grow closer.
We will keep building together. The book, the videos on Watch and the practice exams are here whenever you want to learn with us.
Happy Diwali, and thank you for being part of this journey.
With warmth, Team BricksNotes