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Five Ways No-code Will Make Your Data Engineering Career Skyrocket

The no-code trend is growing dramatically, and no-code tools are the key weapon in your arsenal to set you apart from the crowd and accelerate your career.

• By John Morrell
• August 17, 2022

As organizations have moved their data and analytics to the cloud, the tools and techniques have changed. Data pipelines have gone from ETL to ELT. A modern data stack has broken down the data stack into a group of highly specialized tools -- data loading, data transformation, orchestration, and observability, to name a few. Data models have gone from highly structured -- such as star schemas -- and designed to cover a wide range of analytics to simpler, individualized structures -- such as wide tables -- designed to meet the needs of a specific analytics task.

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Amid all this change, data transformation has remained squarely in the domain of the data engineers and a newly created position called analytics engineer. The primary approach for data transformation and related pipelines has remained the same -- coding in Python or Scala and SQL.

Many data and analytics engineers believe their value comes from their knowledge of technical data pipeline tools such as Spark and skills in programming data pipelines in Python or Scala, and SQL, so they tend to keep the data transformation environment and processes focused on those skills.

In practice, the added value of a data or analytics engineer isn’t just in their programming skills. Their value includes three additional things:

• Their knowledge of the data
• Their ability to coordinate and orchestrate the process to create and manage data flows
• Their skills in reliably getting the data to the analysts and business teams

Many believe their SQL skills allow them to quickly write the appropriate SQL -- and it certainly does -- but no-code data transformation tools make putting together data transformation pipelines even faster, even for the SQL data engineer.

Reliant Funding, a leading provider of alternative funding for small businesses, uses no-code data transformation tools (from Datameer, the company I work for), and found that switching to no-code allowed them to complete data models in a couple of days that previously took them a month to write and test with SQL and Python. An even bigger benefit to Reliant was that the data and analytics teams became leaders, with their data delivery processes highly optimized and smoothly operating.

No-code tools turn data engineers from pure coders and doers into business data strategists and enablers. No-code puts them in command of the process, allowing them to be orchestrators rather than small cogs in big machines that pump out code.

One myth about no-code tools is that you can’t drop down and code if you want to. In reality, good no-code data transformation tools allow you to use the best approach for the job: no-code, write SQL, or combine a bit of both in a single data flow. Good no-code tools will generate optimized SQL for the target data warehouse and expose to you the generated code if you decide you want to tweak it.

A second myth is that no-code tools are just about programming faster. Good no-code data transformation tools provide many additional benefits such as data model sharing and reuse, the easy discovery of data models, data documentation and knowledge sharing, and easier, stronger data governance.

Here are five ways no-code data transformation tools will help your career.

Projects get done faster. Although the Reliant Funding example shows that no-code can be faster than coding, there are additional ways good no-code data transformation tools can accelerate your projects:

• The project workload can be spread across more users, and analytics teams become more self-service
• Projects become better coordinated, and processes become faster and smoother
• There are fewer requirements mismatches and work needing to be redone because projects are shared across workspaces with the entire team
• Data documentation is automated, eliminating the need to go back and document what you have done

You become a leader. Rather than being the coding cog in the analytics cycle, you become the leader and overall orchestrator of the critical data delivery processes. You lead a virtual team that spans the data teams, analytics teams, and business. In the process, you get to demonstrate and grow your leadership skills.

Change management is faster. Analytics requirements often change over time, requiring data model and pipeline changes. Besides delivering projects faster, change management also becomes faster with no-code tools. You can instantly change data models, test them, and redeploy them, making you responsive to the business teams. For example, Reliant Funding saw change management go from several days to hours using no-code data transformation tools.

Data protection and governance become stronger. By managing all the data models in one place and eliminating extra data silos, no-code tools make the data easier to govern, allow for full audits, and give data stronger protection. You then become a hero to your organization's risk and governance officers and can add valuable data governance skills to your resume.

You facilitate data literacy. As a data or analytics engineer, you have tremendous knowledge about the data you work with. This is one area where you have added a great deal of value to the organization. Good no-code data transformation tools help you share this knowledge through data documentation and embedded data catalogs. You then become the guru of data, sharing your wisdom and increasing the data literacy of your company.