If you’re experiencing a strange feeling of déjà vu as you wade through the latest job seeking crusade, you may not have noticed that everyone's an Engineer.

The humble Engineer has become The Holy Grail of modern business. Once a discernable profession, an 'engineering mindset' is now a requirement.

The engineers of today are equally well known to be blazing trails across the technology horizon as they are to be building bricks and mortar.

To be an engineer when I grew up was to be mild mannered, accurate, deeply technical and quietly driven - in a machine-like manner - consistent, enduring, precise.

From Strategic Risk Engineering to Task Engineering. Civil Infrastructure Engineering to Cloud Migration Engineering.

The common denominator is Engineering. Nowadays, everybody’s an Engineer.

What's Going On?

The definition of engineering has been quietly expanded - but at whose expense.

Your once familiar job niche has metastasized into something almost unfamiliar.

• Job titles are obscure.

• Role definitions are often stretched across people, process and systems.

• Strategy and stakeholder management fall neatly into the same sentence as execution and coding.

• Project Management and Leadership alongside architecture and design.

Your role hasn't disappeared or your skills outdated, the scope increased, it now includes engineering thinking and it's no more prominent than in the Data niche.

This is no small thing. I consider myself an expert in a very specific data niche, Data Migration, particularly SAP. With two end to end migrations in recent years, that makes me very experienced with ‘ETL - Extract, Transform, Load’.

ETL - the process of taking a company's data from one place to another.

ETL is a very complex undertaking. It crosses the spectrum of a transformational project, end to end, including:

• Strategy

• Leadership

• Communication

• Execution

• People

• Customers

These requirements are now the bare minimum qualifications, and you won’t get a look in if you’re not an Engineer.

The Engineering Factor

The market has rewritten the rules - tools trump experience.

Roles like these now require expert level expertise in Apps like Snowflake, Databricks, Apache, dbt Labs and a range of other data products whose use, particularly at the Enterprise level, has exploded alongside AI.

Data Warehouses, BI, Big-Data are all nothing new. Data Lakes and Data Highways are common and that’s where these products fit.

SQL for a long time has been a necessity for these complex roles. Where I once ‘got by’ using SQL, I now claim to be a quasi-expert thanks to AI. You may think that's not comparable to a SQL Engineer - I say it is what it is, a SQL query is a SQL query, how you got there is not that important.

My observation around the data niche is that most roles are over-engineered, pun intended. The seemingly pivotal experience that makes or breaks your compatibility, appears to rest disproportionately on experience with packages such as Snowflake.

Doth Snowflake Maketh the Engineer?

If you can’t beat em’ then join em’.

To see what aIl the fuss was about, I built Snowflake into my ‘stack’ so I can use it day to day. It now sits over my entire business, Extracting, Transforming and Loading my data from various events and sources.

I didn't do this to appear 'more engineer-like', I did it to null and void the argument.

The irony of this is by no means lost on me. It turns out that Snowflake is a UI wrapper for an ETL tool with a ton of features, native AI and App development all driven by you guessed it - SQL.

To paraphrase, it’s a familiar cloud-based UI driven by SQL Queries.

If you can drive it, it's yours for the taking.

See more at MGRNZ.com.

Interested in practical AI, automation and better business systems? See what I'm building or contact Mike.