Data Engineer (m/f/d). A competency profile.
Updated: Aug 28
The competency profile validates your domain expertise in data. It recognizes you as a Senior practitioner or advances your career to the Senior level.
By practitioners, for practitioners - this service is provided by AI Guild members recognized for their expertise.
Here is an example of a Data Engineer.
Promit Ray crossed over from a Computational Ph.D. to data engineering, using his skill set to identify use cases suitable for productionization. The interesting combination, in this case, is the STEM Ph.D., the computational skills, the data experience, and the ML skills.
What do you see in the competency profile?
This data engineering profile shows breadth highly relevant to business decision-making. Data Engineering is the focus of all tasks, driving forward a company builder. The particular strength is
Engineering solutions for data analytics with Python and SQL
Visualizing patterns for business decisions
Complementary skills lie in infrastructure management (supporting analytics) and machine learning (supporting use case selection).
Focus: What is in and what has been left out?
The experienced practitioner may infer that the profile indicates a smaller team, hence the wider range of tasks.
Yet, I think the profile shows focus. For all companies, especially startups, the most important task is identifying use cases suitable for machine learning and then choosing wisely which to productionize.
Where is his #datacareer headed?
Business-oriented data engineering is a promising career path. It is more than just data engineering with a focus on data and pipelines because its practice is driven by business development, revenue, and cost considerations. I expect him to proceed on an accelerated career path.
Do you want to progress to Senior, Lead, and Director?
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