Strategy > Syntax
So many tools. Where do you actually start?
How to pick the data engineering stack that gets you hired, using 10 real job postings.
- When
- Wednesday, November 47:00 PM ET / 6:00 PM CT / 4:00 PM PT
- Where
- Live on Google MeetYour link arrives by email when you register.
- With
- Chris GambillFounder, Gambill Data
- Cost
- Free
Can’t make it live? Register anyway. The replay goes out the next morning.
Save your seat in the form below.
Save your free seat
Wednesday, November 4, 7:00 PM ET. The Google Meet link goes to your inbox.
A short list to learn, and a longer list to skip.
- A way to pick your stack from real postings instead of the internet’s list
- A ranked list of the 3 to 5 things to learn next
- A skip list, so you stop spending evenings on the wrong tools
- How to turn that stack into one project you can talk about in an interview
Let the postings write your roadmap.
Snowflake, Databricks, Fabric, Spark, Kafka, dbt, Airflow, three clouds. You wouldn’t learn all of that in 20 years, and you don’t need to. Six steps narrow it down. We do the first three live, together.
- 1Live on the call
Pick one industry
Weighted on your background and the job market first.
- 2Live on the call
Pull 10 postings
From the last 30 days, in the $135K to $185K range.
- 3Live on the call
Tally the skills
Posting by posting, so you see how the counts add up.
- 4
Score yourself
On what you can do fast, with nothing in front of you.
- 5
Find priority gaps
In 7 or more postings, and you rate yourself 3 or lower.
- 6
Write your skip list
If it shows up in 1 out of 10, it can wait.
You’re closer than the course catalog makes you feel.
Analysts and data-adjacent roles
“Pulled the weekly numbers” is often a repeatable ETL process across three source systems. You just never called it that.
Data work on older tools
SQL Server, SSIS, star schemas, under another job title. All of it carries with you. Your gap is scale and platform.
Career changers stuck on courses
Courses teach clean data where nothing breaks. A cert proves you finished a course. It’s a signal, not a solution.
Chris Gambill, founder of Gambill Data
Chris has built data systems, led data teams and hired data engineers. He’s written the postings you’re reading.
This is training, not a job interview. Chris isn’t a recruiter and isn’t hiring for a role. Stay to the end and he’ll show how he works with people, then take your questions.
Register anyway. The replay goes to your inbox on the morning of Thursday, November 5, and comes down at 11:59 PM ET on Wednesday, November 11.
Have one industry in mind before you join. Healthcare, fintech or marketing, for example. We pull postings and build the tally together on the call.
Before you register
Is it really free?
Yes. At the end, Chris explains how he works with people one-on-one and in groups, and the session stays open for questions. There’s no hard stop.
How do I join?
It runs on Google Meet. The link arrives in your confirmation email. You’ll get a reminder on the afternoon of November 4 and another an hour before it starts.
Do I need to know Spark, Kafka or a particular cloud?
No. Part of the session is working out which of those your target postings actually ask for, and which you can skip for now.
Will it work if I’m coming from an analyst role?
Yes. A lot of analyst work is data engineering under a different name. Chris shows how to put that work in the language hiring managers scan for.
Wednesday, November 4, 7:00 PM ET
6:00 PM CT / 4:00 PM PT. Live on Google Meet, free, with a replay the next morning.
Save my seat